2022

1. Journal.

   Learning Sequential Descriptors for Sequence-Based Visual Place Recognition

   Mereu, Riccardo, Trivigno, Gabriele, Berton, Gabriele,  Masone, Carlo, and Caputo, Barbara

   IEEE Robotics and Automation Letters 2022

   Abs arXiv Bib Code

   In robotics, visual place recognition (VPR) is a continuous process that receives as input a video stream to produce a hypothesis of the robot’s current position within a map of known places. This work proposes a taxonomy of the architectures used to learn sequential descriptors for VPR, highlighting different mechanisms to fuse the information from the individual images. This categorization is supported by a complete benchmark of experimental results that provides evidence of the strengths and weaknesses of these different architectural choices. The analysis is not limited to existing sequential descriptors, but we extend it further to investigate the viability of Transformers instead of CNN backbones. We further propose a new ad-hoc sequence-level aggregator called SeqVLAD, which outperforms prior state of the art on different datasets. The code is available at https://github.com/vandal-vpr/vg-transformers.

   @article{MereuTrivigno-2022,
     author = {Mereu, Riccardo and Trivigno, Gabriele and Berton, Gabriele and Masone, Carlo and Caputo, Barbara},
     journal = {IEEE Robotics and Automation Letters},
     title = {Learning Sequential Descriptors for Sequence-Based Visual Place Recognition},
     year = {2022},
     volume = {7},
     number = {4},
     pages = {10383-10390},
     doi = {10.1109/LRA.2022.3194310},
     url = {https://doi.org/10.1109/LRA.2022.3194310},
   }

2. Journal.

   Adaptive-Attentive Geolocalization From Few Queries: A Hybrid Approach

   Paolicelli, Valerio, Berton, Gabriele, Montagna, Francesco,  Masone, Carlo, and Caputo, Barbara

   Frontiers in Computer Science 2022

   Abs Bib PDF

   We tackle the task of cross-domain visual geo-localization, where the goal is to geo-localize a given query image against a database of geo-tagged images, in the case where the query and the database belong to different visual domains. In particular, at training time, we consider having access to only few unlabeled queries from the target domain. To adapt our deep neural network to the database distribution, we rely on a 2-fold domain adaptation technique, based on a hybrid generative-discriminative approach. To further enhance the architecture, and to ensure robustness across domains, we employ a novel attention layer that can easily be plugged into existing architectures. Through a large number of experiments, we show that this adaptive-attentive approach makes the model robust to large domain shifts, such as unseen cities or weather conditions. Finally, we propose a new large-scale dataset for cross-domain visual geo-localization, called SVOX.

   @article{Paolicelli-2022b,
     author = {Paolicelli, Valerio and Berton, Gabriele and Montagna, Francesco and Masone, Carlo and Caputo, Barbara},
     title = {Adaptive-Attentive Geolocalization From Few Queries: A Hybrid Approach},
     journal = {Frontiers in Computer Science},
     volume = {4},
     year = {2022},
     url = {https://www.frontiersin.org/article/10.3389/fcomp.2022.841817},
     doi = {10.3389/fcomp.2022.841817},
     issn = {2624-9898},
   }

3. Workshop Proc.

   Augmentation Invariance and Adaptive Sampling in Semantic Segmentation of Agricultural Aerial Images

   Tavera, A., Arnaudo, E.,  Masone, C., and Caputo, B.

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2022

   Abs arXiv Bib Code

   In this paper, we investigate the problem of Semantic Segmentation for agricultural aerial imagery. We observe that the existing methods used for this task are designed without considering two characteristics of the aerial data: (i) the top-down perspective implies that the model cannot rely on a fixed semantic structure of the scene, because the same scene may be experienced with different rotations of the sensor; (ii) there can be a strong imbalance in the distribution of semantic classes because the relevant objects of the scene may appear at extremely different scales (e.g., a field of crops and a small vehicle). We propose a solution to these problems based on two ideas: (i) we use together a set of suitable augmentation and a consistency loss to guide the model to learn semantic representations that are invariant to the photometric and geometric shifts typical of the top-down perspective (Augmentation Invariance); (ii) we use a sampling method (Adaptive Sampling) that selects the training images based on a measure of pixel-wise distribution of classes and actual network confidence. With an extensive set of experiments conducted on the Agriculture-Vision dataset, we demonstrate that our proposed strategies improve the performance of the current state-of-the-art method.

   @inproceedings{Tavera-2022,
     author = {Tavera, A. and Arnaudo, E. and Masone, C. and Caputo, B.},
     title = {Augmentation Invariance and Adaptive Sampling in Semantic Segmentation of Agricultural Aerial Images},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
     year = {2022},
     pages = {},
   }

4. Conference Proc.

   Learning Semantics for Visual Place Recognition through Multi-Scale Attention

   Paolicelli, V., Tavera, A., Berton, G.,  Masone, C., and Caputo, B.

   In Proceedings of the 21st International Conference on Image Analysis and Processing (ICIAP) 2022

   Abs arXiv Bib

   In this paper we address the task of visual place recognition (VPR), where the goal is to retrieve the correct GPS coordinates of a given query image against a huge geotagged gallery. While recent works have shown that building descriptors incorporating semantic and appearance information is beneficial, current state-of-the-art methods opt for a top down definition of the significant semantic content. Here we present the first VPR algorithm that learns robust global embeddings from both visual appearance and semantic content of the data, with the segmentation process being dynamically guided by the recognition of places through a multi-scale attention module. Experiments on various scenarios validate this new approach and demonstrate its performance against state-of-the-art methods. Finally, we propose the first synthetic-world dataset suited for both place recognition and segmentation tasks.

   @inproceedings{Paolicelli-2022,
     author = {Paolicelli, V. and Tavera, A. and Berton, G. and Masone, C. and Caputo, B.},
     title = {Learning Semantics for Visual Place Recognition through Multi-Scale Attention},
     booktitle = {Proceedings of the 21st International Conference on Image Analysis and Processing (ICIAP)},
     year = {2022},
     pages = {},
   }

5. Conference Proc.

   Rethinking Visual Geo-localization for Large-Scale Applications

   Berton, G.,  Masone, C., and Caputo, B.

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022

   Abs arXiv Bib Code

   Visual Geo-localization (VG) is the task of estimating the position where a given photo was taken by comparing it with a large database of images of known locations. To investigate how existing techniques would perform on a real-world city-wide VG application, we build San Francisco eXtra Large, a new dataset covering a whole city and providing a wide range of challenging cases, with a size 30x bigger than the previous largest dataset for visual geo-localization. We find that current methods fail to scale to such large datasets, therefore we design a new highly scalable training technique, called CosPlace, which casts the training as a classification problem avoiding the expensive mining needed by the commonly used contrastive learning. We achieve state-of-the-art performance on a wide range of datasets and find that CosPlace is robust to heavy domain changes. Moreover, we show that, compared to the previous state-of-the-art, CosPlace requires roughly 80% less GPU memory at train time, and it achieves better results with 8x smaller descriptors, paving the way for city-wide real-world visual geo-localization.

   @inproceedings{Berton-2022,
     author = {Berton, G. and Masone, C. and Caputo, B.},
     title = {Rethinking Visual Geo-localization for Large-Scale Applications},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     year = {2022},
     pages = {},
   }

6. Conference Proc. Oral

   Deep Visual Geo-localization Benchmark

   Berton, G., Mereu, R., Trivigno, G.,  Masone, C., Csurka, G., Sattler, T., and Caputo, B.

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022

   Abs arXiv Bib Code

   In this paper, we propose a new open-source benchmarking framework for Visual Geo-localization (VG) that allows to build, train, and test a wide range of commonly used architectures, with the flexibility to change individual components of a geo-localization pipeline. The purpose of this framework is twofold: i) gaining insights into how different components and design choices in a VG pipeline impact the final results, both in terms of performance (recall@N metric) and system requirements (such as execution time and memory consumption); ii) establish a systematic evaluation protocol for comparing different methods. Using the proposed framework, we perform a large suite of experiments which provide criteria for choosing backbone, aggregation and negative mining depending on the use-case and requirements. We also assess the impact of engineering techniques like pre/post-processing, data augmentation and image resizing, showing that better performance can be obtained through somewhat simple procedures: for example, downscaling the images’ resolution to 80% can lead to similar results with a 36% savings in extraction time and dataset storage requirement.

   @inproceedings{Berton-2022b,
     author = {Berton, G. and Mereu, R. and Trivigno, G. and Masone, C. and Csurka, G. and Sattler, T. and Caputo, B.},
     title = {Deep Visual Geo-localization Benchmark},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     year = {2022},
     pages = {},
   }

7. Conference Proc.

   Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation

   Tavera, A., Cermelli, F.,  Masone, C., and Caputo, B.

   In 2022 IEEE Winter Conference on Applications of Computer Vision (WACV) 2022

   Abs arXiv Bib HTML Code

   In this paper we consider the task of semantic segmentation in autonomous driving applications. Specifically, we consider the cross-domain few-shot setting where training can use only few real-world annotated images and many annotated synthetic images. In this context, aligning the domains is made more challenging by the pixel-wise class imbalance that is intrinsic in the segmentation and that leads to ignoring the underrepresented classes and overfitting the well represented ones. We address this problem with a novel framework called Pixel-By-Pixel Cross-Domain Alignment (PixDA). We propose a novel pixel-by-pixel domain adversarial loss following three criteria: (i) align the source and the target domain for each pixel, (ii) avoid negative transfer on the correctly represented pixels, and (iii) regularize the training of infrequent classes to avoid overfitting. The pixel-wise adversarial training is assisted by a novel sample selection procedure, that handles the imbalance between source and target data, and a knowledge distillation strategy, that avoids overfitting towards the few target images. We demonstrate on standard synthetic-to-real benchmarks that PixDA outperforms previous state-of-the-art methods in (1-5)-shot settings.

   @inproceedings{Tavera-2022b,
     author = {Tavera, A. and Cermelli, F. and Masone, C. and Caputo, B.},
     title = {Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation},
     booktitle = {2022 IEEE Winter Conference on Applications of Computer Vision (WACV)},
     year = {2022},
     pages = {1626-1635},
   }

2021

1. Conference Proc.

   Adaptive-Attentive Geolocalization from few queries: a hybrid approach

   Moreno Berton, G., Paolicelli, V.,  Masone, C., and Caputo, B.

   In 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) 2021

   Abs arXiv Bib HTML Code

   We address the task of cross-domain visual place recognition, where the goal is to geolocalize a given query image against a labeled gallery, in the case where the query and the gallery belong to different visual domains. To achieve this, we focus on building a domain robust deep network by leveraging over an attention mechanism combined with few-shot unsupervised domain adaptation techniques, where we use a small number of unlabeled target domain images to learn about the target distribution. With our method, we are able to outperform the current state of the art while using two orders of magnitude less target domain images. Finally we propose a new large-scale dataset for cross-domain visual place recognition, called SVOX.

   @inproceedings{Berton-2021,
     author = {{Moreno Berton}, G. and Paolicelli, V. and Masone, C. and Caputo, B.},
     booktitle = {2021 IEEE Winter Conference on Applications of Computer Vision (WACV)},
     title = {Adaptive-Attentive Geolocalization from few queries: a hybrid approach},
     year = {2021},
     volume = {},
     number = {},
     pages = {2917-2926},
     doi = {10.1109/WACV48630.2021.00296},
   }

2. Conference Proc.

   Reimagine BiSeNet for Real-Time Domain Adaptation in Semantic Segmentation

   Tavera, A.,  Masone, C., and Caputo, B.

   In Proceedings of the I-RIM 2021 Conference 2021

   Abs arXiv Bib Code

   Semantic segmentation models have reached remarkable performance across various tasks. However, this performance is achieved with extremely large models, using powerful computational resources and without considering training and inference time. Real-world applications, on the other hand, necessitate models with minimal memory demands, efficient inference speed, and executable with low-resources embedded devices, such as self-driving vehicles. In this paper, we look at the challenge of real-time semantic segmentation across domains, and we train a model to act appropriately on real-world data even though it was trained on a synthetic realm. We employ a new lightweight and shallow discriminator that was specifically created for this purpose. To the best of our knowledge, we are the first to present a real-time adversarial approach for assessing the domain adaption problem in semantic segmentation. We tested our framework in the two standard protocol: GTA5 to Cityscapes and SYNTHIA to Cityscapes.

   @inproceedings{Tavera-2021,
     author = {Tavera, A. and Masone, C. and Caputo, B.},
     title = {Reimagine BiSeNet for Real-Time Domain Adaptation in Semantic Segmentation},
     booktitle = {Proceedings of the I-RIM 2021 Conference},
     year = {2021},
     pages = {},
   }

3. Conference Proc.

   Viewpoint Invariant Dense Matching for Visual Geolocalization

   Berton, G.,  Masone, C., Paolicelli, V., and Caputo, B.

   In 2021 IEEE/CVF International Conference on Computer Vision (ICCV) 2021

   Abs arXiv Bib HTML Code

   In this paper we propose a novel method for image matching based on dense local features and tailored for visual geolocalization. Dense local features matching is robust against changes in illumination and occlusions, but not against viewpoint shifts which are a fundamental aspect of geolocalization. Our method, called GeoWarp, directly embeds invariance to viewpoint shifts in the process of extracting dense features. This is achieved via a trainable module which learns from the data an invariance that is meaningful for the task of recognizing places. We also devise a new self-supervised loss and two new weakly supervised losses to train this module using only unlabeled data and weak labels. GeoWarp is implemented efficiently as a re-ranking method that can be easily embedded into pre-existing visual geolocalization pipelines. Experimental validation on standard geolocalization benchmarks demonstrates that GeoWarp boosts the accuracy of state-of-the-art retrieval architectures.

   @inproceedings{Berton-2021b,
     author = {Berton, G. and Masone, C. and Paolicelli, V. and Caputo, B.},
     booktitle = {2021 IEEE/CVF International Conference on Computer Vision (ICCV)},
     title = {Viewpoint Invariant Dense Matching for Visual Geolocalization},
     year = {2021},
     volume = {},
     number = {},
     pages = {12149-12158},
     doi = {10.1109/ICCV48922.2021.01195},
   }

4. Journal

   Shared Control of an Aerial Cooperative Transportation System with a Cable-suspended Payload

   Masone, C., and Stegagno, P.

   Journal of Intelligent & Robotic Systems 2021

   Abs Bib HTML PDF Video

   This paper presents a novel bilateral shared framework for a cooperative aerial transportation and manipulation system composed by a team of micro aerial vehicles with a cable-suspended payload. The human operator is in charge of steering the payload and he/she can also change online the desired shape of the formation of robots. At the same time, an obstacle avoidance algorithm is in charge of avoiding collisions with the static environment. The signals from the user and from the obstacle avoidance are blended together in the trajectory generation module, by means of a tracking controller and a filter called dynamic input boundary (DIB). The DIB filters out the directions of motions that would bring the system too close to singularities, according to a suitable metric. The loop with the user is finally closed with a force feedback that is informative of the mismatch between the operator’s commands and the trajectory of the payload. This feedback intuitively increases the user’s awareness of obstacles or configurations of the system that are close to singularities. The proposed framework is validated by means of realistic hardware-in-the-loop simulations with a person operating the system via a force-feedback haptic interface.

   @article{Masone-2021b,
     author = {Masone, C. and Stegagno, P.},
     journal = {Journal of Intelligent & Robotic Systems},
     title = {Shared Control of an Aerial Cooperative Transportation System with a Cable-suspended Payload},
     year = {2021},
     volume = {103},
     number = {40},
     pages = {},
     doi = {10.1007/s10846-021-01457-4},
   }

5. Journal

   A Survey on Deep Visual Place Recognition

   Masone, C., and Caputo, B.

   IEEE Access 2021

   Abs Bib HTML PDF

   In recent years visual place recognition (VPR), i.e., the problem of recognizing the location of images, has received considerable attention from multiple research communities, spanning from computer vision to robotics and even machine learning. This interest is fueled on one hand by the relevance that visual place recognition holds for many applications and on the other hand by the unsolved challenge of making these methods perform reliably in different conditions and environments. This paper presents a survey of the state-of-the-art of research on visual place recognition, focusing on how it has been shaped by the recent advances in deep learning. We start discussing the image representations used in this task and how they have evolved from using hand-crafted to deep-learned features. We further review how metric learning techniques are used to get more discriminative representations, as well as techniques for dealing with occlusions, distractors, and shifts in the visual domain of the images. The survey also provides an overview of the specific solutions that have been proposed for applications in robotics and with aerial imagery. Finally the survey provides a summary of datasets that are used in visual place recognition, highlighting their different characteristics.

   @article{Masone-2021,
     author = {Masone, C. and Caputo, B.},
     journal = {IEEE Access},
     title = {A Survey on Deep Visual Place Recognition},
     year = {2021},
     volume = {9},
     number = {},
     pages = {19516-19547},
     doi = {10.1109/ACCESS.2021.3054937},
   }

2020

1. Journal

   IDDA: A Large-Scale Multi-Domain Dataset for Autonomous Driving

   Alberti, E., Tavera, A.,  Masone, C., and Caputo, B.

   IEEE Robotics and Automation Letters 2020

   Abs arXiv Bib HTML Code

   Semantic segmentation is key in autonomous driving. Using deep visual learning architectures is not trivial in this context, because of the challenges in creating suitable large scale annotated datasets. This issue has been traditionally circumvented through the use of synthetic datasets, that have become a popular resource in this field. They have been released with the need to develop semantic segmentation algorithms able to close the visual domain shift between the training and test data. Although exacerbated by the use of artificial data, the problem is extremely relevant in this field even when training on real data. Indeed, weather conditions, viewpoint changes and variations in the city appearances can vary considerably from car to car, and even at test time for a single, specific vehicle. How to deal with domain adaptation in semantic segmentation, and how to leverage effectively several different data distributions (source domains) are important research questions in this field. To support work in this direction, this letter contributes a new large scale, synthetic dataset for semantic segmentation with more than 100 different source visual domains. The dataset has been created to explicitly address the challenges of domain shift between training and test data in various weather and view point conditions, in seven different city types. Extensive benchmark experiments assess the dataset, showcasing open challenges for the current state of the art.

   @article{Alberti-2020,
     author = {Alberti, E. and Tavera, A. and Masone, C. and Caputo, B.},
     journal = {IEEE Robotics and Automation Letters},
     title = {IDDA: A Large-Scale Multi-Domain Dataset for Autonomous Driving},
     year = {2020},
     volume = {5},
     number = {4},
     pages = {5526-5533},
     doi = {10.1109/LRA.2020.3009075},
   }

2018

1. Book Chapter

   Application of a Differentiator-Based Adaptive Super-Twisting Controller for a Redundant Cable-Driven Parallel Robot

   Schenk, C.,  Masone, C., Pott, A., and Bülthoff, Heinrich H.

   In Cable-Driven Parallel Robots 2018

   Abs Bib HTML

   In this paper we present preliminary, experimental results of an Adaptive Super-Twisting Sliding-Mode Controller with time-varying gains for redundant Cable-Driven Parallel Robots. The sliding-mode controller is paired with a feed-forward action based on dynamics inversion. An exact sliding-mode differentiator is implemented to retrieve the velocity of the end-effector using only encoder measurements with the properties of finite-time convergence, robustness against perturbations and noise filtering. The platform used to validate the controller is a robot with eight cables and six degrees of freedom powered by 940W compact servo drives. The proposed experiment demonstrates the performance of the controller, finite-time convergence and robustness in tracking a trajectory while subject to external disturbances up to approximately 400% the mass of the end-effector.

   @inproceedings{Schenk-2018,
     author = {Schenk, C. and Masone, C. and Pott, A. and Bülthoff, Heinrich H.},
     editor = {Gosselin, C. and Cardou, P. and Bruckmann, T. and Pott, A.},
     title = {Application of a Differentiator-Based Adaptive Super-Twisting Controller for a Redundant Cable-Driven Parallel Robot},
     booktitle = {Cable-Driven Parallel Robots},
     year = {2018},
     publisher = {Springer International Publishing},
     address = {Cham},
     pages = {254-267},
   }

2. Journal

   Shared planning and control for mobile robots with integral haptic feedback

   Masone, C., Mohammadi, M., Robuffo Giordano, P., and Franchi, A.

   The International Journal of Robotics Research 2018

   Abs Bib HTML PDF

   This paper presents a novel bilateral shared framework for online trajectory generation for mobile robots. The robot navigates along a dynamic path, represented as a B-spline, whose parameters are jointly controlled by a human supervisor and an autonomous algorithm. The human steers the reference (ideal) path by acting on the path parameters that are also affected, at the same time, by the autonomous algorithm to ensure: (i) collision avoidance, (ii) path regularity, and (iii) proximity to some points of interest. These goals are achieved by combining a gradient descent-like control action with an automatic algorithm that re-initializes the traveled path (replanning) in cluttered environments to mitigate the effects of local minima. The control actions of both the human and the autonomous algorithm are fused via a filter that preserves a set of local geometrical properties of the path to ease the tracking task of the mobile robot. The bilateral component of the interaction is implemented via a force feedback that accounts for both human and autonomous control actions along the whole path, thus providing information about the mismatch between the reference and traveled path in an integral sense. The proposed framework is validated by means of realistic simulations and actual experiments deploying a quadrotor unmanned aerial vehicle (UAV) supervised by a human operator acting via a force-feedback haptic interface. Finally, a user study is presented to validate the effectiveness of the proposed framework and the usefulness of the provided force cues.

   @article{Masone-2018,
     author = {Masone, C. and Mohammadi, M. and {Robuffo Giordano}, P. and Franchi, A.},
     title = {Shared planning and control for mobile robots with integral haptic feedback},
     journal = {The International Journal of Robotics Research},
     volume = {37},
     number = {11},
     pages = {1395-1420},
     year = {2018},
     doi = {10.1177/0278364918802006},
   }

2016

1. Conference Proc. Award

   The CableRobot simulator large scale motion platform based on cable robot technology

   Miermeister, P., Lächele, M., Boss, R.,  Masone, C., Schenk, C., Tesch, J., Kerger, M., Teufel, H., Pott, A., and Bülthoff, H. H.

   In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016

   Abs Award Bib HTML Video

   This paper introduces the CableRobot simulator, which was developed at the Max Planck Institute for Biological Cybernetics in cooperation with the Fraunhofer Institute for Manufacturing Engineering and Automation IPA. The simulator is a completely novel approach to the design of motion simulation platforms in so far as it uses cables and winches for actuation instead of rigid links known from hexapod simulators. This approach allows to reduce the actuated mass, scale up the workspace significantly, and provides great flexibility to switch between system configurations in which the robot can be operated. The simulator will be used for studies in the field of human perception research and virtual reality applications. The paper discusses some of the issues arising from the usage of cables and provides a system overview regarding kinematics and system dynamics as well as giving a brief introduction into possible application use cases.

   Winner of the IROS JTCF Novel Technology Paper Award for Amusement Culture

   @inproceedings{Miermeister-2016,
     author = {Miermeister, P. and Lächele, M. and Boss, R. and Masone, C. and Schenk, C. and Tesch, J. and Kerger, M. and Teufel, H. and Pott, A. and Bülthoff, H. H.},
     booktitle = {2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
     title = {The CableRobot simulator large scale motion platform based on cable robot technology},
     year = {2016},
     volume = {},
     number = {},
     pages = {3024-3029},
     doi = {10.1109/IROS.2016.7759468},
   }

2. Conference Proc.

   Cooperative transportation of a payload using quadrotors: A reconfigurable cable-driven parallel robot

   Masone, C., Bülthoff, H. H., and Stegagno, P.

   In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016

   Abs Bib HTML PDF

   This paper addresses the problem of cooperative aerial transportation of an object using a team of quadrotors. The approach presented to solve this problem accounts for the full dynamics of the system and it is inspired by the literature on reconfigurable cable-driven parallel robots (RCDPR). Using the modelling convention of RCDPR it is derived a direct relation between the motion of the quadrotors and the motion of the payload. This relation makes explicit the available internal motion of the system, which can be used to automatically achieve additional tasks. The proposed method does not require to specify a priory the forces in the cables and uses a tension distribution algorithm to optimally distribute them among the robots. The presented framework is also suitable for online teleoperation. Physical simulations with a human-in-the-loop validate the proposed approach.

   @inproceedings{Masone-2016,
     author = {Masone, C. and Bülthoff, H. H. and Stegagno, P.},
     booktitle = {2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
     title = {Cooperative transportation of a payload using quadrotors: A reconfigurable cable-driven parallel robot},
     year = {2016},
     volume = {},
     number = {},
     pages = {1623-1630},
     doi = {10.1109/IROS.2016.7759262},
   }

3. Conference Proc. Award

   Modeling and analysis of cable vibrations for a cable-driven parallel robot

   Schenk, C.,  Masone, C., Miermeister, P., and Bülthoff, H. H.

   In 2016 IEEE International Conference on Information and Automation (ICIA) 2016

   Abs Award Bib HTML PDF

   In this paper we study if approximated linear models are accurate enough to predict the vibrations of a cable of a Cable-Driven Parallel Robot (CDPR) for different pretension levels. In two experiments we investigated the damping of a thick steel cable from the Cablerobot simulator and measured the motion of the cable when a sinusoidal force is applied at one end of the cable. Using this setup and power spectral density analysis we measured the natural frequencies of the cable and compared these results to the frequencies predicted by two linear models: i) the linearization of partial differential equations of motion for a distributed cable, and ii) the discretization of the cable using a finite elements model. This comparison provides remarkable insights into the limits of approximated linear models as well as important properties of vibrating cables used in CDPR.

   Best Paper award Finalist

   @inproceedings{Schenk-2016,
     author = {Schenk, C. and Masone, C. and Miermeister, P. and Bülthoff, H. H.},
     booktitle = {2016 IEEE International Conference on Information and Automation (ICIA)},
     title = {Modeling and analysis of cable vibrations for a cable-driven parallel robot},
     year = {2016},
     volume = {},
     number = {},
     pages = {454-461},
     doi = {10.1109/ICInfA.2016.7831867},
   }

4. Conference Proc.

   Adaptive Super Twisting Controller for a quadrotor UAV

   Rajappa, S.,  Masone, C., Bülthoff, H. H., and Stegagno, P.

   In 2016 IEEE International Conference on Robotics and Automation (ICRA) 2016

   Abs Bib HTML

   In this paper we present a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using the recently proposed gain adaptation law [1], [2], which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The higher order quadrotor dynamic model and proposed controller are validated using a SimMechanics physical simulation with initial error, parameter uncertainties, noisy measurements and external perturbations.

   @inproceedings{Rajappa-2016,
     author = {Rajappa, S. and Masone, C. and Bülthoff, H. H. and Stegagno, P.},
     booktitle = {2016 IEEE International Conference on Robotics and Automation (ICRA)},
     title = {Adaptive Super Twisting Controller for a quadrotor UAV},
     year = {2016},
     volume = {},
     number = {},
     pages = {2971-2977},
     doi = {10.1109/ICRA.2016.7487462},
   }

2015

1. Conference Proc.

   Robust adaptive sliding mode control of a redundant cable driven parallel robot

   Schenk, C., Bülthoff, H. H., and Masone, C.

   In 2015 19th International Conference on System Theory, Control and Computing (ICSTCC) 2015

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   In this paper we consider the application problem of a redundant cable-driven parallel robot, tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using a recently proposed gains adaptation law [1], thus not requiring the knowledge of the upper bound of the lumped uncertainties. The controller is extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. Compared to a recently developed Adaptive Terminal Sliding Mode Controller for cable-driven parallel robots [2], the proposed controller manages to achieve lower tracking errors and less chattering in the actuation forces even in presence of perturbations. The system is implemented and tested in simulation using a model of a large redundant cable-driven robot and assuming noisy measurements. Simulations show the effectiveness of the proposed method.

   @inproceedings{Schenk-2015,
     author = {Schenk, C. and Bülthoff, H. H. and Masone, C.},
     booktitle = {2015 19th International Conference on System Theory, Control and Computing (ICSTCC)},
     title = {Robust adaptive sliding mode control of a redundant cable driven parallel robot},
     year = {2015},
     volume = {},
     number = {},
     pages = {427-434},
     doi = {10.1109/ICSTCC.2015.7321331},
   }

2014

1. Conference Proc.

   Semi-autonomous trajectory generation for mobile robots with integral haptic shared control

   Masone, C., Robuffo Giordano, P., Bülthoff, H. H., and Franchi, A.

   In 2014 IEEE International Conference on Robotics and Automation (ICRA) 2014

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   A new framework for semi-autonomous path planning for mobile robots that extends the classical paradigm of bilateral shared control is presented. The path is represented as a B-spline and the human operator can modify its shape by controlling the motion of a finite number of control points. An autonomous algorithm corrects in real time the human directives in order to facilitate path tracking for the mobile robot and ensures i) collision avoidance, ii) path regularity, and iii) attraction to nearby points of interest. A haptic feedback algorithm processes both human’s and autonomous control terms, and their integrals, to provide an information of the mismatch between the path specified by the operator and the one corrected by the autonomous algorithm. The framework is validated with extensive experiments using a quadrotor UAV and a human in the loop with two haptic interfaces.

   @inproceedings{Masone-2014,
     author = {Masone, C. and {Robuffo Giordano}, P. and Bülthoff, H. H. and Franchi, A.},
     booktitle = {2014 IEEE International Conference on Robotics and Automation (ICRA)},
     title = {Semi-autonomous trajectory generation for mobile robots with integral haptic shared control},
     year = {2014},
     volume = {},
     number = {},
     pages = {6468-6475},
     doi = {10.1109/ICRA.2014.6907814},
   }

2012

1. Journal

   Modeling and Control of UAV Bearing Formations with Bilateral High-level Steering

   Franchi, A.,  Masone, C., Grabe, V., Ryll, M., Bülthoff, H. H., and Robuffo Giordano, P.

   The International Journal of Robotics Research 2012

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   In this paper we address the problem of controlling the motion of a group of unmanned aerial vehicles (UAVs) bound to keep a formation defined in terms of only relative angles (i.e. a bearing formation). This problem can naturally arise within the context of several multi-robot applications such as, e.g. exploration, coverage, and surveillance. First, we introduce and thoroughly analyze the concept and properties of bearing formations, and provide a class of minimally linear sets of bearings sufficient to uniquely define such formations. We then propose a bearing-only formation controller requiring only bearing measurements, converging almost globally, and maintaining bounded inter-agent distances despite the lack of direct metric information.The controller still leaves the possibility of imposing group motions tangent to the current bearing formation. These can be either autonomously chosen by the robots because of any additional task (e.g. exploration), or exploited by an assisting human co-operator. For this latter ’human-in-the-loop’ case, we propose a multi-master/multi-slave bilateral shared control system providing the co-operator with some suitable force cues informative of the UAV performance. The proposed theoretical framework is extensively validated by means of simulations and experiments with quadrotor UAVs equipped with onboard cameras. Practical limitations, e.g. limited field-of-view, are also considered.

   @article{Franchi-2012,
     author = {Franchi, A. and Masone, C. and Grabe, V. and Ryll, M. and Bülthoff, H. H. and {Robuffo Giordano}, P.},
     title = {Modeling and Control of UAV Bearing Formations with Bilateral High-level Steering},
     journal = {The International Journal of Robotics Research},
     volume = {31},
     number = {12},
     pages = {1504-1525},
     year = {2012},
     doi = {10.1177/0278364912462493},
   }

2. Conference Proc.

   Interactive planning of persistent trajectories for human-assisted navigation of mobile robots

   Masone, C., Franchi, A., Bülthoff, H. H., and Robuffo Giordano, P.

   In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems 2012

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   This work extends the framework of bilateral shared control of mobile robots with the aim of increasing the robot autonomy and decreasing the operator commitment. We consider persistent autonomous behaviors where a cyclic motion must be executed by the robot. The human operator is in charge of modifying online some geometric properties of the desired path. This is then autonomously processed by the robot in order to produce an actual path guaranteeing: i) tracking feasibility, ii) collision avoidance with obstacles, iii) closeness to the desired path set by the human operator, and iv) proximity to some points of interest. A force feedback is implemented to inform the human operator of the global deformation of the path rather than using the classical mismatch between desired and executed motion commands. Physically-based simulations, with human/hardware-in-the-loop and a quadrotor UAV as robotic platform, demonstrate the feasibility of the method.

   @inproceedings{Masone-2012,
     author = {Masone, C. and Franchi, A. and Bülthoff, H. H. and {Robuffo Giordano}, P.},
     booktitle = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
     title = {Interactive planning of persistent trajectories for human-assisted navigation of mobile robots},
     year = {2012},
     volume = {},
     number = {},
     pages = {2641-2648},
     doi = {10.1109/IROS.2012.6386171},
   }

3. Conference Proc.

   Roll rate thresholds and perceived realism in driving simulation

   Nesti, A.,  Masone, C., Barnett-Cowan, M., Robuffo Giordano, P., Bülthoff, H. H., and Pretto, P.

   In Driving Simulation Conference 2012 2012

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   Due to limited operational space, in dynamic driving simulators it is common practice to implement motion cueing algorithms that tilt the simulator cabin to reproduce sustained accelerations. In order to avoid conflicting inertial cues, the tilt rate is kept below drivers’ perceptual thresholds, which are typically derived from the results of classical vestibular research where additional sensory cues to self-motion are removed. Here we conduct two experiments in order to assess whether higher tilt limits can be employed to expand the user’s perceptual workspace of dynamic driving simulators. In the first experiment we measure detection thresholds for roll in conditions that closely resemble typical driving. In the second experiment we measure drivers’ perceived realism in slalom driving for sub-, near- and supra-threshold roll rates. Results show that detection threshold for roll in an active driving task is remarkably higher than the limits currently used in motion cueing algorithms to drive simulators. Supra-threshold roll rates in the slalom task are also rated as more realistic. Overall, our findings suggest that higher tilt limits can be successfully implemented in motion cueing algorithms to better optimize simulator operational space.

   @inproceedings{Nesti-2012,
     author = {Nesti, A. and Masone, C. and Barnett-Cowan, M. and {Robuffo Giordano}, P. and Bülthoff, H. H. and Pretto, P.},
     booktitle = {Driving Simulation Conference 2012},
     title = {Roll rate thresholds and perceived realism in driving simulation},
     year = {2012},
     volume = {},
     number = {},
     pages = {23-31},
     doi = {},
   }

2011

1. Conference Proc.

   Bilateral teleoperation of multiple UAVs with decentralized bearing-only formation control

   Franchi, A.,  Masone, C., Bülthoff, H. H., and Robuffo Giordano, P.

   In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems 2011

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   We present a decentralized system for the bilateral teleoperation of groups of UAVs which only relies on relative bearing measurements, i.e., without the need of distance information or global localization. The properties of a 3D bearing-formation are analyzed, and a minimal set of bearings needed for its definition is provided. We also design a novel decentralized formation control almost globally convergent and able to maintain bounded and non-vanishing inter-distances among the agents despite the absence of direct distance measurements. Furthermore, we develop a multi-master/ multi-slave teleoperation setup in order to control the overall behavior of the group and to convey to the human operator suitable force cues, while ensuring stability in presence of delays and packet losses over the master-slave communication channel. The theoretical framework is validated by means of extensive human/hardware in-the-loop simulations using two force-feedback devices and a group of quadrotors.

   @inproceedings{Franchi-2011,
     author = {Franchi, A. and Masone, C. and Bülthoff, H. H. and {Robuffo Giordano}, P.},
     booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
     title = {Bilateral teleoperation of multiple UAVs with decentralized bearing-only formation control},
     year = {2011},
     volume = {},
     number = {},
     pages = {2215-2222},
     doi = {10.1109/IROS.2011.6094525},
   }

2. Conference Proc.

   Mechanical design and control of the new 7-DOF CyberMotion simulator

   Masone, C., Robuffo Giordano, P., and Bülthoff, H. H.

   In 2011 IEEE International Conference on Robotics and Automation 2011

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   This paper describes the mechanical and control design of the new 7-DOF CyberMotion Simulator, a redundant industrial manipulator arm consisting of a standard 6-DOF anthropomorphic manipulator plus an actuated cabin attached to the end-effector. Contrarily to Stewart platforms, an industrial manipulator offers several advantages when used as motion simulator: larger motion envelope, higher dexterity, and possibility to realize any end-effector posture within the workspace. In addition to this, the new actuated cabin acts as an additional joint and provides the needed kinematic redundancy to cope with the robot actuator and joint range constraints, which in general can significantly deteriorate the desired motion cues the robot is reproducing. In particular, we will show that, by suitably exploiting the redundancy better results can be obtained in reproducing sustained acceleration cues, a relevant problem when implementing vehicle simulators.

   @inproceedings{Masone-2011,
     author = {Masone, C. and {Robuffo Giordano}, P. and Bülthoff, H. H.},
     booktitle = {2011 IEEE International Conference on Robotics and Automation},
     title = {Mechanical design and control of the new 7-DOF CyberMotion simulator},
     year = {2011},
     volume = {},
     number = {},
     pages = {4935-4942},
     doi = {10.1109/ICRA.2011.5980436},
   }

2010

1. Conference Proc.

   A novel framework for closed-loop robotic motion simulation - part II: Motion cueing design and experimental validation

   Robuffo Giordano, P.,  Masone, C., Tesch, J., Breidt, M., Pollini, L., and Bülthoff, H. H.

   In 2010 IEEE International Conference on Robotics and Automation 2010

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   This paper, divided in two Parts, considers the problem of realizing a 6-DOF closed-loop motion simulator by exploiting an anthropomorphic serial manipulator as motion platform. After having proposed a suitable inverse kinematics scheme in Part I [1], we address here the other key issue, i.e., devising a motion cueing algorithm tailored to the specific robot motion envelope. An extension of the well-known classical washout filter designed in cylindrical coordinates will provide an effective solution to this problem. The paper will then present a thorough experimental evaluation of the overall architecture (inverse kinematics + motion cueing) on the chosen scenario: closed-loop simulation of a Formula 1 racing car. This will prove the feasibility of our approach in fully exploiting the robot motion capabilities as a motion simulator.

   @inproceedings{Robuffo-2010b,
     author = {{Robuffo Giordano}, P. and Masone, C. and Tesch, J. and Breidt, M. and Pollini, L. and Bülthoff, H. H.},
     booktitle = {2010 IEEE International Conference on Robotics and Automation},
     title = {A novel framework for closed-loop robotic motion simulation - part II: Motion cueing design and experimental validation},
     year = {2010},
     volume = {},
     number = {},
     pages = {3896-3903},
     doi = {10.1109/ROBOT.2010.5509945},
   }

2. Conference Proc.

   A novel framework for closed-loop robotic motion simulation - part I: Inverse kinematics design

   Robuffo Giordano, P.,  Masone, C., Tesch, J., Breidt, M., Pollini, L., and Bülthoff, H. H.

   In 2010 IEEE International Conference on Robotics and Automation 2010

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   This paper considers the problem of realizing a 6-DOF closed-loop motion simulator by exploiting an anthropomorphic serial manipulator as motion platform. Contrary to standard Stewart platforms, an industrial anthropomorphic manipulator offers a considerably larger motion envelope and higher dexterity that let envisage it as a viable and superior alternative. Our work is divided in two papers. In this Part I, we discuss the main challenges in adopting a serial manipulator as motion platform, and thoroughly analyze one key issue: the design of a suitable inverse kinematics scheme for online motion reproduction. Experimental results are proposed to analyze the effectiveness of our approach. Part II [1] will address the design of a motion cueing algorithm tailored to the robot kinematics, and will provide an experimental evaluation on the chosen scenario: closed-loop simulation of a Formula 1 racing car.

   @inproceedings{Robuffo-2010,
     author = {Robuffo Giordano, P. and Masone, C. and Tesch, J. and Breidt, M. and Pollini, L. and Bülthoff, H. H.},
     booktitle = {2010 IEEE International Conference on Robotics and Automation},
     title = {A novel framework for closed-loop robotic motion simulation - part I: Inverse kinematics design},
     year = {2010},
     volume = {},
     number = {},
     pages = {3876-3883},
     doi = {10.1109/ROBOT.2010.5509647},
   }