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Customizing Textile and Tactile Skins for Interactive Industrial Robots

ASME Letters in Dynamic Systems and control 2023年第3期3卷 031007页

作者： Su, Bo Ying Wei, Zhongqi McCann, James Yuan, Wenzhen Liu, Changliu Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA 15213 Robotics Institute Carnegie Mellon University Pittsburgh PA 15213

Tactile skins made from textiles enhance the robot–human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating, calibrating, and deploying these skins on industrial robot arms. The novel automated skin calibration procedure maps skin locations to robot geometry and calibrates contact force. Through experiments on a FANUC LR Mate 200id/7L industrial robot, we demonstrate that tactile skins made from textiles can be effectively used for human–robot interaction in industrial environments, and can provide unique opportunities in robot control and learning, making them a promising technology for enhancing robot perception and interaction.

关键词： Robots sensors and sensor networks Calibration textile and tactile skin Textiles Skin interactive industrial robots skin calibration human-in-the-loop control robotics

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Evaluation of a machine-learning-driven active-passive upper-limb exoskeleton robot: Experimental human-in-the-loop study

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WEARABLE TECHNOLOGIES 2023年第1期4卷 e13页

作者： Nasr, Ali Hunter, Jason Dickerson, Clark R. Mcphee, John Univ Waterloo Syst Design Engn Waterloo ON N2L 3G1 Canada Univ Waterloo Kinesiol & Hlth Sci Waterloo ON Canada

Evaluating exoskeleton actuation methods and designing an effective controller for these exoskeletons are both challenging and time-consuming tasks. This is largely due to the complicated human-robot interactions, the selection of sensors and actuators, electrical/command connection issues, and communication delays. In this research, a test framework for evaluating a new active-passive shoulder exoskeleton was developed, and a surface electromyography (sEMG)-based human-robot cooperative control method was created to execute the wearer's movement intentions. The hierarchical control used sEMG-based intention estimation, mid-level strength regulation, and low-level actuator control. It was then applied to shoulder joint elevation experiments to verify the exoskeleton controller's effectiveness. The active-passive assistance was compared with fully passive and fully active exoskeleton control using the following criteria: (1) post-test survey, (2) load tolerance duration, and (3) computed human torque, power, and metabolic energy expenditure using sEMG signals and inverse dynamic simulation. The experimental outcomes showed that active-passive exoskeletons required less muscular activation torque (50%) from the user and reduced fatigue duration indicators by a factor of 3, compared to fully passive ones.

关键词： Wearable robots exoskeletons active-passive assistive control human-in-the-loop control

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Real-Time Stylized humanoid Behavior control through Interaction and Synchronization

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SENSORS 2022年第4期22卷 1457-1457页

作者： Cao, Zhiyan Bao, Tianxu Ren, Zeyu Fan, Yunxin Deng, Ken Jia, Wenchuan Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200444 Peoples R China Beijing Univ Posts & Telecommun Inst Wireless Theories & Technol Lab Beijing 100876 Peoples R China

Restricted by the diversity and complexity of human behaviors, simulating a character to achieve human-level perception and motion control is still an active as well as a challenging area. We present a style-based teleoperation framework with the help of human perceptions and analyses to understand the tasks being handled and the unknown environment to control the character. In this framework, the motion optimization and body controller with center-of-mass and root virtual control (CR-VC) method are designed to achieve motion synchronization and style mimicking while maintaining the balance of the character. The motion optimization synthesizes the human high-level style features with the balance strategy to create a feasible, stylized, and stable pose for the character. The CR-VC method including the model-based torque compensation synchronizes the motion rhythm of the human and character. Without any inverse dynamics knowledge or offline preprocessing, our framework is generalized to various scenarios and robust to human behavior changes in real-time. We demonstrate the effectiveness of this framework through the teleoperation experiments with different tasks, motion styles, and operators. This study is a step toward building a human-robot interaction that uses humans to help characters understand and achieve the tasks.

关键词： character animation human-robot interaction teleoperation control human-in-the-loop control

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AR-assisted digital twin-enabled robot collaborative manufacturing system with human-in-the-loop

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2022年第0期76卷 102321-102321页

作者： Li, Chengxi Zheng, Pai Li, Shufei Pang, Yatming Lee, Carman K. M. Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Peoples R China Lab Artificial Intelligence Design New Terr Hong Kong Sci Pk Hong Kong Peoples R China

The teleoperation and coordination of multiple industrial robots play an important role in today's industrial internet-based collaborative manufacturing systems. The user-friendly teleoperation approach allows operators from different manufacturing domains to reduce redundant learning costs and intuitively control the robot in advance. Nevertheless, only a few preliminary works have been introduced very recently, let alone its effective implementation in the manufacturing scenarios. To address the gap, this research proposes a novel multi-robot collaborative manufacturing system with human-in-the-loop control by leveraging the cutting edge augmented reality (AR) and digital twin (DT) techniques. In the proposed system, the DTs of industrial robots are firstly mapped to physical robots and visualize them in the AR glasses. Meanwhile, a multi-robot communication mechanism is designed and implemented, to synchronize the state of robots in the twin. Moreover, a reinforcement learning algorithm is integrated into the robot motion planning to replace the conventional kinematics-based robot movement with corresponding target positions. Finally, three interactive AR-assisted DT modes, including real-time motion control, planned motion control, and robot monitoring mode are generated, which can be readily switched by human operators. Two experimental studies are conducted on (1) a single robot with a commonly used peg-in-hole experiment, and (2) the motion planning of multi-robot collaborative tasks, respectively. From the experimental results, it can be found that the proposed system can well handle the multi-robot teleoperation tasks with high efficiency and owns great potentials to be adopted in other complicated manufacturing scenarios in the near future.

关键词： Augmented reality Digital twin Collaborative manufacturing system Reinforcement learning human-in-the-loop control

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SENSORS 2022年第5期22卷 1968-1968页

作者： Gong, Liang Chen, Binhao Xu, Wenbin Liu, Chengliang Li, Xudong Zhao, Zelin Zhao, Lujie Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China

Precisely imitating human motions in real-time poses a challenge for the robots due to difference in their physical structures. This paper proposes a human-computer interaction method for remotely manipulating life-size humanoid robots with a new metrics for evaluating motion similarity. First, we establish a motion capture system to acquire the operator's motion data and retarget it to the standard bone model. Secondly, we develop a fast mapping algorithm, by mapping the BVH (BioVision Hierarchy) data collected by the motion capture system to each joint motion angle of the robot to realize the imitated motion control of the humanoid robot. Thirdly, a DTW (Dynamic Time Warping)-based trajectory evaluation method is proposed to quantitatively evaluate the difference between robot trajectory and human motion, and meanwhile, visualization terminals render it more convenient to make comparisons between two different but simultaneous motion systems. We design a complex gesture simulation experiment to verify the feasibility and real-time performance of the control method. The proposed human-in-the-loop imitation control method addresses a prominent non-isostructural retargeting problem between human and robot, enhances robot interaction capability in a more natural way, and improves robot adaptability to uncertain and dynamic environments.

关键词： motion imitation life-size humanoid robot BioVision hierarchy motion capture DTW-based trajectory evaluation human-in-the-loop control

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control Interface for Hands-free Navigation of Standing Mobility Vehicles based on Upper-Body Natural Movements

Control Interface for Hands-free Navigation of Standing Mobi...

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

作者： Chen, Yang Paez-Granados, Diego Kadone, Hideki Suzuki, Kenji Univ Tsukuba Sch Integrat & Global Majors SIGMA Tsukuba Ibaraki Japan Ecole Polytech Fed Lausanne EPFL Learning Algorithms & Syst Lab LASA Lausanne Switzerland Univ Tsukuba Hosp Ctr Innovat Med & Engn Tsukuba Ibaraki Japan Univ Tsukuba Fac Engn Tsukuba Ibaraki Japan Univ Tsukuba Ctr Cybern Res Tsukuba Ibaraki Japan

ISBN: (纸本)9781728162126

In this paper, we propose and evaluate a novel human-machine interface (HMI) for controlling a standing mobility vehicle or person carrier robot, aiming for a hands-free control through upper-body natural postures derived from gaze tracking while walking. We target users with lower-body impairment with remaining upper-body motion capabilities. The developed HMI bases on a sensing array for capturing body postures;an intent recognition algorithm for continuous mapping of body motions to robot control space;and a personalizing system for multiple body sizes and shapes. We performed two user studies: first, an analysis of the required body muscles involved in navigating with the proposed control;and second, an assessment of the HMI compared with a standard joystick through quantitative and qualitative metrics in a narrow circuit task. We concluded that the main user control contribution comes from Rectus Abdominis and Erector Spinae muscle groups at different levels. Finally, the comparative study showed that a joystick still outperforms the proposed HMI in usability perceptions and controllability metrics, however, the smoothness of user control was similar in jerk and fluency. Moreover, users' perceptions showed that hands-free control made it more anthropomorphic, animated, and even safer.

关键词： Medical robotics human-robot interaction human-machine interface design human-in-the-loop control

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Context and Driver Dependent Hybrid Electrical Vehicle Operation 3rd

Context and Driver Dependent Hybrid Electrical Vehicle Opera...

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3rd IFAC Workshop pn Cyber-Physical and human Systems (CPHS)

作者： Cajo, Ricardo Bengea, Sorin Beck, Rian Dwek, Nathan Meskens, Joram Venkatesan, Sudarsan K. Plaza, Douglas De Keyser, Robin Ionescu, Clara M. Univ Ghent Dept Electromech Syst & Met Engn Tech Lane Sci Pk 125 B-9052 Ghent Belgium Flanders Make Consortium EEDT Decis & Control Tech Lane Sci Pk 131 B-9052 Ghent Belgium Escuela Super Politecn Litoral ESPOL Fac Ingn Elect & Comp Campus Gustavo Galindo Km 30-5 Via Perimetral Guayaquil 090150 Ecuador Flanders Make Decis & Control Gaston Geenslaan 8 B-3001 Heverlee Belgium

This paper studies the driver and context changes during the operation of a hybrid electric vehicle (HEV) and their influence on fuel consumption. Firstly, a context estimation model to recognize driving styles is developed based on machine learning techniques, for which a realistic scenario with simulation of urban mobility (SUMO) and car modeling platform (IPG Carmaker) integration is designed. Secondly, a novel context-aware control strategy based on model predictive control with extended prediction self-adaptive control (MPC-EPSAC) strategy is proposed. The control objective is to achieve optimal torque-split distribution, while optimizing fuel consumption in the parallel HEV. The simulation results suggest that an improvement in fuel economy can be achieved when the driving style in the control loop is adequately considered. Copyright (C) 2020 The Authors.

关键词： Context aware control Context estimation Machine learning human-in-the-loop control Cyber physical systems Model predictive control (MPC) Self-optimization

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Driver-Automation Cooperation Oriented Approach for Shared control of Lane Keeping Assist Systems

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IEEE TRANSACTIONS ON control SYSTEMS TECHNOLOGY 2019年第5期27卷 1962-1978页

作者： Sentouh, Chouki Anh-Tu Nguyen Benloucif, Mohamed Amir Popieul, Jean-Christophe Univ Polytech Hauts de France CNRS UMR 8201 Lab Automat Mecan & Informat Ind & Humaines LAMIH F-59300 Valenciennes France

This paper presents a novel shared control concept for lane keeping assist (LKA) systems of intelligent vehicles. The core idea is to combine system perception with robust control so that the proposed strategy can successfully share the control authority between human drivers and the LKA system. This shared control strategy is composed of two parts, namely an operational part and a tactical part. Two local optimal-based controllers with two predefined objectives (i.e., lane keeping and conflict management) are designed in the operational part. The control supervisor in the tactical part aims to provide a decision-making signal which allows for a smooth transition between two local controllers. The control design is based on a human-in-the-loop vehicle system to improve the mutual driver-automation understanding, thus reducing or avoiding the conflict. The closed-loop stability of the whole driver-vehicle system can be rigorously guaranteed using the Lyapunov stability argument. In particular, the control design is formulated as an LMI optimization which can be easily solved with numerical solvers. The effectiveness of the proposed shared control method is clearly demonstrated through various hardware experiments with human drivers.

关键词： Advanced driver assistance systems (ADASs) control authority transition human-in-the-loop control linear matrix inequality (LMI) shared control vehicle control

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Passivity-Based Bilateral Tele-Driving System With Parametric Uncertainty and Communication Delays

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IEEE control SYSTEMS LETTERS 2019年第2期3卷 350-355页

作者： Dong, Yimeng Chopra, Nikhil Univ Maryland Dept Mech Engn College Pk MD 20740 USA

In this letter, a new bilateral tele-driving control design is proposed to enable a human driver to tele-drive a car-like mobile robot with haptic feedback. In the presence of communication delays and dynamic parametric uncertainties, a passivity-based adaptive control algorithm is designed to achieve scaled coordination between a local and a remote robot. The efficacy of the proposed control scheme is verified through numerical simulations.

关键词： human-in-the-loop control control over communications

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Vector Autoregressive POMDP Model Learning and Planning for human-Robot Collaboration

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IEEE control SYSTEMS LETTERS 2019年第3期3卷 775-780页

作者： Zheng, Wei Lin, Hai Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA

human-robot collaboration (HRC) has emerged as a hot research area at the intersection of control, robotics, and psychology in recent years. It is of critical importance to obtain an expressive but meanwhile tractable model for human beings in HRC. In this letter, we propose a model called vector autoregressive partially observable Markov decision process (VAR-POMDP) which is an extension of the traditional POMDP model by considering the correlation among observations. The VAR-POMDP model is more powerful in the expressiveness of features than the traditional continuous observation POMDP since the traditional one is a special case of the VAR-POMDP model. Meanwhile, the proposed VAR-POMDP model is also tractable, as we show that it can be effectively learned from data and we can extend point-based value iteration (PBVI) to VAR-POMDP planning. Particularly, in this letter, we propose to use the Bayesian non-parametric learning to decide potential human states and learn a VAR-POMDP model using data collected from human demonstrations. Then, we consider planning with respect to PCTL which is widely used as safety and reachability requirement in robotics. Finally, the advantage of using the proposed model for HRC is validated by experimental results using data collected from a driver-assistance test-bed.

关键词： Autonomous systems human-in-the-loop control machine learning modeling

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