Publications

by Keyword: Robot sensing systems


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Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., Puigbo, J., Pattacini, U., Low, S. C., Camilleri, D., Nguyen, P., Hoffmann, M., Chang, H. J., Zambelli, M., Mealier, A., Damianou, A., Metta, G., Prescott, T. J., Demiris, Y., Dominey, P. F., Verschure, P. F. M. J., (2018). DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self IEEE Transactions on Cognitive and Developmental Systems in press

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

Keywords: Autobiographical Memory., Biology, Cognition, Cognitive Robotics, Computer architecture, Distributed Adaptive Control, Grounding, Human-Robot Interaction, Humanoid robots, Robot sensing systems, Symbol Grounding


Aviles, A. I., Alsaleh, S. M., Sobrevilla, P., Casals, A., (2015). Force-feedback sensory substitution using supervised recurrent learning for robotic-assisted surgery Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 1-4

The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.

Keywords: Computer architecture, Estimation, Force, Microprocessors, Robot sensing systems, Surgery


Mur, O., Frigola, M., Casals, A., (2015). Modelling daily actions through hand-based spatio-temporal features ICAR 2015 International Conference on Advanced Robotics , IEEE (Istanbul, Turkey) , 478-483

In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.

Keywords: Histograms, Joints, Robot sensing systems, Thumb, Tracking, Human activity recognition, Disable and elderly assistance


Aviles, A. I., Alsaleh, S., Sobrevilla, P., Casals, A., (2015). Sensorless force estimation using a neuro-vision-based approach for robotic-assisted surgery NER 2015 7th International IEEE/EMBS Conference on Neural Engineering , IEEE (Montpellier, France) , 86-89

This paper addresses the issue of lack of force feedback in robotic-assisted minimally invasive surgeries. Force is an important measure for surgeons in order to prevent intra-operative complications and tissue damage. Thus, an innovative neuro-vision based force estimation approach is proposed. Tissue surface displacement is first measured via minimization of an energy functional. A neuro approach is then used to establish a geometric-visual relation and estimate the applied force. The proposed approach eliminates the need of add-on sensors, carrying out biocompatibility studies and is applicable to tissues of any shape. Moreover, we provided an improvement from 15.14% to 56.16% over other approaches which demonstrate the potential of our proposal.

Keywords: Estimation, Force, Minimally invasive surgery, Robot sensing systems, Three-dimensional displays


Hernandez Bennetts, V. M., Lilienthal, A. J., Khaliq, A. A., Pomareda Sese, V., Trincavelli, M., (2013). Towards real-world gas distribution mapping and leak localization using a mobile robot with 3d and remote gas sensing capabilities 2013 IEEE International Conference on Robotics and Automation (ICRA) (ed. Parker, Lynne E.), IEEE (Karlsruhe, Germany) , 2335-2340

Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor. This sensor provides integral concentration measurements over the path of the laser beam. Existing gas distribution mapping algorithms can only handle local measurements obtained from traditional in-situ chemical sensors. In this paper we also describe an algorithm to generate 3D methane concentration maps from integral concentration and depth measurements. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.

Keywords: Laser beams, Measurement by laser beam, Mobile robots, Robot kinematics, Robot sensing systems


Antelis, J.M., Montesano, L., Giralt, X., Casals, A., Minguez, J., (2012). Detection of movements with attention or distraction to the motor task during robot-assisted passive movements of the upper limb Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6410-6413

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb


Amigo, L. E., Fernandez, Q., Giralt, X., Casals, A., Amat, J., (2012). Study of patient-orthosis interaction forces in rehabilitation therapies IEEE Conference Publications 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) , IEEE (Roma, Italy) , 1098-1103

The design of mechanical joints that kinematically behave as their biological counterparts is a challenge that if not addressed properly can cause inadequate forces transmission between robot and patient. This paper studies the interaction forces in rehabilitation therapies of the elbow joint. To measure the effect of orthosis-patient misalignments, a force sensor with a novel distributed architecture has been designed and used for this study. A test-bed based on an industrial robot acting as a virtual exoskeleton that emulates the action of a therapist has been developed and the interaction forces analyzed.

Keywords: Force, Force measurement, Force sensors, Joints, Medical treatment, Robot sensing systems, Force sensors, Medical robotics, Patient rehabilitation, Biological counterparts, Distributed architecture, Elbow joint, Force sensor, Inadequate forces transmission, Industrial robot, Mechanical joints design, Orthosis-patient misalignments, Patient-orthosis interaction forces, Rehabilitation therapies, Robot, Test-bed, Virtual exoskeleton