Sharing the Load: Human-Robot Team Lifting Using Muscle Activity

Seamless communication of desired motions and goals is essential for enabling effective physical human-robot collaboration. In such cases, muscle activity measured via surface electromyography (EMG) can provide insight into a person’s intentions while minimally distracting from the task. The presented system uses two muscle signals to create a control framework for team lifting tasks in which a human and robot lift an object together. A continuous setpoint algorithm uses biceps activity to estimate changes in the user’s hand height, and also allows the user to explicitly adjust the robot by stiffening or relaxing their arm. In addition to this pipeline, a neural network trained only on previous users classifies biceps and triceps activity to detect up or down gestures on a rolling basis; this enables finer control over the robot and expands the feasible workspace. The resulting system is evaluated by 10 untrained subjects performing a variety of team lifting and assembly tasks with rigid and flexible objects.

[1]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[2]  F. Zajac.  Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. , 1989, Critical reviews in biomedical engineering.

[3]  Paul E. Spector,et al.  The Impact of Cross-Training on Team Functioning: An Empirical Investigation , 1996, Hum. Factors.

[4]  Elliot E. Entin,et al.  Adaptive Team Coordination , 1999, Hum. Factors.

[5]  C. J. Luca,et al.  SURFACE ELECTROMYOGRAPHY : DETECTION AND RECORDING , 2022 .

[6]  K. Manal,et al.  A one-parameter neural activation to muscle activation model: estimating isometric joint moments from electromyograms. , 2003, Journal of biomechanics.

[7]  Toshio Fukuda,et al.  Neuro-fuzzy control of a robotic exoskeleton with EMG signals , 2004, IEEE Transactions on Fuzzy Systems.

[8]  Yoky Matsuoka,et al.  Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[9]  Robin R. Murphy,et al.  Human-robot interaction in rescue robotics , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[10]  J. Gregory Trafton,et al.  Enabling effective human-robot interaction using perspective-taking in robots , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[11]  Blake Hannaford,et al.  Hill-Based Model as a Myoprocessor for a Neural Controlled Powered Exoskeleton Arm - Parameters Optimization , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[12]  Rajesh P. N. Rao,et al.  Real-Time Classification of Electromyographic Signals for Robotic Control , 2005, AAAI.

[13]  G. Gini,et al.  An EMG-controlled exoskeleton for hand rehabilitation , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[14]  Charles C. Kemp,et al.  Human-Robot Interaction for Cooperative Manipulation: Handing Objects to One Another , 2007, RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication.

[15]  Alois Knoll,et al.  Joint-action for humans and industrial robots for assembly tasks , 2008, RO-MAN 2008 - The 17th IEEE International Symposium on Robot and Human Interactive Communication.

[16]  Elisabeth André,et al.  EMG-based hand gesture recognition for realtime biosignal interfacing , 2008, IUI '08.

[17]  Max E Valentinuzzi,et al.  Robust EMG sensing system based on data fusion for myoelectric control of a robotic arm , 2009, Biomedical engineering online.

[18]  Paul Evrard,et al.  Teaching physical collaborative tasks: object-lifting case study with a humanoid , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[19]  Kazuo Kiguchi,et al.  SUEFUL-7: A 7DOF upper-limb exoskeleton robot with muscle-model-oriented EMG-based control , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Sandra Hirche,et al.  Load sharing in human-robot cooperative manipulation , 2010, 19th International Symposium in Robot and Human Interactive Communication.

[21]  Panagiotis K. Artemiadis,et al.  EMG-Based Control of a Robot Arm Using Low-Dimensional Embeddings , 2010, IEEE Transactions on Robotics.

[22]  Nicola Vitiello,et al.  Proportional EMG control for upper-limb powered exoskeletons , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  Sandra Hirche,et al.  Towards interactive physical robotic assistance: Parameterizing motion primitives through natural language , 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

[24]  Stefanos Nikolaidis,et al.  Optimization of Temporal Dynamics for Adaptive Human-Robot Interaction in Assembly Manufacturing , 2012, Robotics: Science and Systems.

[25]  Stefanos Nikolaidis,et al.  Human-robot cross-training: Computational formulation, modeling and evaluation of a human team training strategy , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[26]  D. S. V. Bandara,et al.  Recent Trends in EMG-Based Control Methods for Assistive Robots , 2013 .

[27]  Tadej Petric,et al.  Teaching robots to cooperate with humans in dynamic manipulation tasks based on multi-modal human-in-the-loop approach , 2014, Auton. Robots.

[28]  Przemyslaw A. Lasota,et al.  Toward safe close-proximity human-robot interaction with standard industrial robots , 2014, 2014 IEEE International Conference on Automation Science and Engineering (CASE).

[29]  Don Joven Agravante,et al.  Collaborative human-humanoid carrying using vision and haptic sensing , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[30]  Brian Charles Williams,et al.  Concurrent Plan Recognition and Execution for Human-Robot Teams , 2014, ICAPS.

[31]  Joao Luiz A. S. Ramos,et al.  Use of surface electromyography for human amplification using an exoskeleton driven by artificial pneumatic muscles , 2014, 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics.

[32]  Julie A. Shah,et al.  Fast target prediction of human reaching motion for cooperative human-robot manipulation tasks using time series classification , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[33]  M. Rostami,et al.  A hill-based EMG-driven model to estimate elbow torque during flexion and extention , 2015, 2015 22nd Iranian Conference on Biomedical Engineering (ICBME).

[34]  Oussama Khatib,et al.  A parameterized family of anatomically accurate human upper-body musculoskeletal models for dynamic simulation & control , 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

[35]  Arash Ajoudani,et al.  A Human–Robot Co-Manipulation Approach Based on Human Sensorimotor Information , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[36]  Javier Alonso-Mora,et al.  Multi-robot formation control and object transport in dynamic environments via constrained optimization , 2017, Int. J. Robotics Res..

[37]  Joseph DelPreto,et al.  Plug-and-play supervisory control using muscle and brain signals for real-time gesture and error detection , 2018, Autonomous Robots.