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IEEE TRANSACTIONS ON MEDICAL robotics AND BIONICS 2021年第4期3卷 888-899页

作者： Falezza, Fabio Piccinelli, Nicola De Rossi, Giacomo Roberti, Andrea Kronreif, Gernot Setti, Francesco Fiorini, Paolo Muradore, Riccardo Univ Verona Dept Comp Sci I-37134 Verona Italy ACMIT Gmbh A-2700 Wiener Neustadt Austria

In this paper we propose a new methodology to model surgical procedures that is specifically tailored to semi-autonomous robotic surgery. We propose to use a restricted version of statecharts to merge the bottom-up approach, based on data-driven techniques (e.g., machine learning), with the top-down approach based on knowledge representation techniques. We consider medical knowledge about the procedure and sensing of the environment in two concurrent regions of the statecharts to facilitate re-usability and adaptability of the modules. Our approach allows producing a well defined procedural model exploiting the hierarchy capability of the statecharts, while machine learning modules act as soft sensors to trigger state transitions. Integrating data driven and prior knowledge techniques provides a robust, modular, flexible and re-configurable methodology to define a surgical procedure which is comprehensible by both humans and machines. We validate our approach on the three surgical phases of a Robot-Assisted Radical Prostatectomy (RARP) that directly involve the assistant surgeon: bladder mobilization, bladder neck transection, and vesicourethral anastomosis, all performed on synthetic manikins.

关键词： Surgical robotics statecharts supervisory controller autonomous robotics

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Behavioural plasticity in evolving robots

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THEORY IN BIOSCIENCES 2016年第4期135卷 201-216页

作者： Carvalho, Jonata Tyska Nolfi, Stefano CNR Inst Cognit Sci & Technol Via S Martino Battaglia 44 I-00185 Rome Italy Fed Univ Rio Grande Ctr Computat Sci C3 Av ItaliaKm 8 BR-96203900 Rio Grande Brazil

In this paper, we show how the development of plastic behaviours, i.e., behaviour displaying a modular organisation characterised by behavioural subunits that are alternated in a context-dependent manner, can enable evolving robots to solve their adaptive task more efficiently also when it does not require the accomplishment of multiple conflicting functions. The comparison of the results obtained in different experimental conditions indicates that the most important prerequisites for the evolution of behavioural plasticity are: the possibility to generate and perceive affordances (i.e., opportunities for behaviour execution), the possibility to rely on flexible regulatory processes that exploit both external and internal cues, and the possibility to realise smooth and effective transitions between behaviours.

关键词： Behavioural plasticity Evolutionary robotics Multiple behaviours autonomous robotics Modularity Action switching

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Recognition and Pose Estimation of Auto Parts for an autonomous Spray Painting Robot

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2019年第3期15卷 1709-1719页

作者： Lin, Weiyang Anwar, Ali Li, Zhan Tong, Mingsi Qiu, Jianbin Gao, Huijun Harbin Inst Technol State Key Lab Robot & Syst Key Lab Microsyst & Microstruct Mfg Minist Educ Harbin 150001 Heilongjiang Peoples R China Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150001 Heilongjiang Peoples R China

The autonomous operation of industrial robots with minimal human supervision has always been in high demand. To prepare the autonomous operation of a car part spray painting robot, novel object detection, and pose estimation algorithms have been developed in this paper. The object detection part used principal components analysis (PCA) to reduce the dimension of three-dimensional (3-D) point cloud to 2-D binary image. Distance measure between the auto and cross correlation of the binary features was established to find out the similarity between them. Resultantly, the type of auto part was successfully obtained. Furthermore, iterative closest point (ICP) algorithm was used to estimate the pose difference of the auto part with respect to the camera reference frame, which was mounted on the robot. An issue with ICP's lack of robustness to local minimum was solved by the combination of ICP and genetic algorithm (GA). This allowed the optimization of pose error and addressed the problem of local minimum entrapment in ICP. For experimental validation: the proposed object recognition pipeline was implemented in both serial and parallel programming paradigms. The results were obtained for the acquired point clouds of side body car parts and compared with the major 3-D object detection systems in terms of computational cost. Pose estimation error was calculated with both ICP and the modified point set registration schemes, and it was shown to be decreasing in the case of later. All shown results supported the research claims.

关键词： autonomous robotics principal components analysis spray painting robot three-dimensional object recognition visual servoing

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Structural control using a deployable autonomous control system

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INTERNATIONAL JOURNAL OF INTELLIGENT robotics AND APPLICATIONS 2017年第3期1卷 306-326页

作者： Goorts, Kevin Phillips, Stephen Ashasi-Sorkhabi, Ali Narasimhan, Sriram Univ Waterloo Dept Civil & Environm Engn Waterloo ON Canada

Structural control devices facilitate the construction of lightweight structures by suppressing excessive vibrations that arise from the reduced self-weight. Most of the current structural control systems are permanent installations designed to control particular structural properties and are hence specific to a particular application. This paper presents a novel concept of a deployable, autonomous control system (DACS) targeting specific applications where short-term vibration mitigation is desired. These applications may include control of existing structures during predictable extreme loading events or temporary structures where the need for vibration mitigation depends on usage characteristics. This control system consists of an electromechanical mass damper (EMD) mounted on an unmanned ground vehicle (UGV) equipped with vision sensors. The mobility of the UGV combined with on-board vision sensors facilitates autonomous positioning of the device at any desired location of the structure. This allows the device to update its position on the structure as required, through a simultaneous localization and mapping (SLAM) solution, to effectively control different structural modes. The performance of the SLAM solution is evaluated using a full-scale pedestrian bridge while the ability of the proposed system to re-position itself to control various modes of vibration is studied through real-time hybrid simulation (RTHS). The experimental results confirm the ability of the proposed system to effectively control large amplitude motion in slender bridges, while being able to position itself at the appropriate locations for multi-modal control. The concept of the overall system presents promising results for applications where temporary control is desired.

关键词： autonomous robotics EKF-SLAM Active structural control Mobile control system

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Computation of Empowerment for an autonomous Underwater Vehicle

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IFAC-PapersOnLine 2016年第15期49卷 81-87页

作者： Catenacci Volpi, Nicola De Palma, Daniela Polani, Daniel Indiveri, Giovanni Department of Computer Science University of Hertfordshire United Kingdom Dipartimento Ingegneria Innovazione University of Salento – ISME LecceNode-73100 Italy

The paper addresses the computation of the information-theoretic empowerment measure for a simplified vertical plane dynamic model of an eFolaga autonomous underwater vehicle. Empowerment can be used to measure how much influence a vehicle has on its behavior, and it identifies desirable states of the vehicle, hence it can act as an intrinsic cost function to use during a mission. Online empowerment computation can be exploited within complex autonomous robotics missions. The proposed approach is being developed in the framework of a H2020 underwater robotics research project (Widely scalable Mobile Underwater Sonar Technology) to improve the autonomy of autonomous underwater vehicles for acoustic seismic applications. © 2016

关键词： autonomous underwater vehicles Carrier mobility Computation theory Cost functions Information theory robotics Underwater acoustics Acoustic Seismic autonomous robotics Empowerment Marine robotics Of autonomous underwater vehicles Underwater robotics Underwater sonars Vertical plane

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Using the Rhythm of Nonverbal Human-Robot Interaction as a Signal for Learning

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IEEE TRANSACTIONS ON autonomous MENTAL DEVELOPMENT 2011年第1期3卷 30-42页

作者： Andry, Pierre Blanchard, Arnaud Gaussier, Philippe Univ Cergy Pontoise ETIS F-95000 Cergy Pontoise France

Human-robot interaction is a key issue in order to build robots for everyone. The difficulty for people to understand how robots work and how they must be controlled will be one of the mains limit for broad robotics. In this paper, we study a new way of interacting with robots without needing to understand how robots work or to give them explicit instructions. This work is based on psychological data showing that synchronization and rhythm are very important features for pleasant interaction. We propose a biologically inspired architecture using rhythm detection to build an internal reward for learning. After showing the results of keyboard interactions, we present and discuss the results of real human-robots (Aibo and Nao) interactions. We show that our minimalist control architecture allows the discovery and learning of arbitrary sensorimotor associations games with expert users. With nonexpert users, we show that using only the rhythm information is not sufficient for learning all the associations due to the different strategies used by the human. Nevertheless, this last experiment shows that the rhythm is still allowing the discovery of subsets of associations, being one of the promising signal of tomorrow social applications.

关键词： Artificial neural networks autonomous robotics human-robot interaction rhythm detection and prediction self-supervised learning

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Encoder-free odometric system for autonomous microrobots

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MECHATRONICS 2012年第6期22卷 870-880页

作者： Kernbach, Serge Univ Stuttgart Inst Parallel & Distributed High Performance Syst D-70569 Stuttgart Germany

This paper describes an odometric system for autonomous microrobots based on the optical properties of a motor-wheel transmission for motion feedback. We demonstrate that infra-red light, reflected from this mechanical system, shows distinctive periodic changes of amplitude, correlated with the motion of the robot. Real-time odometric signal processing, performed on a small embedded microcontroller, allows accurate movement detection for each wheel and is used for motion control, self-calibration, and calculation of differential and absolute velocity, displacement and rotation. We demonstrate some applications of this on-board odometric system in swarm robot experiments. This approach can also be applied to other industrial or academic mechatronic systems, where size or computational power are limiting factors. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Motion feedback Odometry autonomous robotics Self-calibration Robot swarm

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RoboboITS: A Simulation-Based Tutoring System to Support AI Education Through robotics 24th

RoboboITS: A Simulation-Based Tutoring System to Support AI ...

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24th International Conference on Artificial Intelligence in Education (AIED)

作者： Guerreiro-Santalla, S. Crompton, H. Bellas, F. Univ A Coruna CITIC Res Ctr La Coruna Spain Old Dominion Univ Norfolk VA USA

ISBN: (纸本)9783031363351;9783031363368

This paper presents a novel tutoring system to educate pre-university students about AI, a key issue to develop AI in Education for Sustainable Society. With the aim of following a learning-by-doing approach to AI, we decided to focus on robotics as the main application domain for the students' activities. Specifically, the tutoring system is based on the Robobo educational robot, and its simulation environment. A prototype version of the tutoring system, called RoboboITS, has been released and tested in two in-person sessions with 17 students in a secondary school at Virginia (USA), leading to and promising outcomes for future development.

关键词： AI education AI for K12 Personalized Learning Tutoring Systems Learning by Doing autonomous robotics Robotic Simulation

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Towards A Framework For Dancing Beyond Demonstration 22

Towards A Framework For Dancing Beyond Demonstration

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8th International Conference on Movement and Computing (MOCO)

作者： Martin, Patrick J. Sicchio, Kate Dietzel, Charles Olivo, Alicia Virginia Commonwealth Univ Dept Elect & Comp Engn Richmond VA 23284 USA Virginia Commonwealth Univ Dept Dance & Choreog Richmond VA 23284 USA Virginia Commonwealth Univ Dept Mech & Nucl Engn Richmond VA USA

ISBN: (纸本)9781450387163

This paper presents a prototype framework for developing real-time human-robot performances and its application within a recent choreographic work for the stage. The framework allows dancers to teach new motions to robots, while also giving choreographers the ability to compose performances from pre-built and learned behaviors. To achieve this capability, we combine behavior-based robotics and learning from demonstration approaches to construct behaviors and compose them into a performance. Our learning algorithm, dancing-from-demonstration (DfD), allows dancers and choreographers to teach new phrases to the robot and specify choreographic motifs for the performance. This collaborative work culminated in a human-robot duet, where the robot incorporates a new, learned motion into its choreography within live performance. These capabilities create a baseline for choreographers and dancers to eventually compose and perform in more dynamic, reactive choreo-robotic performances.

关键词： autonomous robotics choreography learning-from-demonstration

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Dynamic Neural Fields as Building Blocks of a Cortex-Inspired Architecture for Robotic Scene Representation

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IEEE TRANSACTIONS ON autonomous MENTAL DEVELOPMENT 2011年第1期3卷 74-91页

作者： Zibner, Stephan K. U. Faubel, Christian Iossifidis, Ioannis Schoener, Gregor Ruhr Univ Bochum Inst Neuroinformat D-44780 Bochum Germany Hsch Ruhr W Muhlheim Inst Informat D-44780 Bochum Germany

Based on the concepts of dynamic field theory (DFT), we present an architecture that autonomously generates scene representations by controlling gaze and attention, creating visual objects in the foreground, tracking objects, reading them into working memory, and taking into account their visibility. At the core of this architecture are three-dimensional dynamic neural fields (DNFs) that link feature to spatial information. These three-dimensional fields couple into lower dimensional fields, which provide the links to the sensory surface and to the motor systems. We discuss how DNFs can be used as building blocks for cognitive architectures, characterize the critical bifurcations in DNFs, as well as the possible coupling structures among DNFs. In a series of robotic experiments, we demonstrate how the DNF architecture provides the core functionalities of a scene representation.

关键词： autonomous robotics dynamic field theory (DFT) dynamical systems embodied cognition neural processing

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