Human Arm Posture Optimisation in Bilateral Teleoperation Through Interface Reconfiguration

In this paper, we propose a method for improving the human operator’s arm posture during bilateral teleoperation. The method is based on a musculoskeletal model that considers human operator’s arm dynamics and the feedback force from the haptic interface (master), which is used to control a robotic arm (slave) in a remote environment. We perform an online optimisation to find the optimal configuration that has the longest endurance time with respect to muscle fatigue. Next, a trajectory is generated on the haptic interface in order to guide the human arm into the optimal configuration. The teleoperation is temporarily suspended by decoupling the master from the slave robot when the haptic device is being reconfigured. Afterwards, the loop is coupled again and the slave robot is controlled from the position where it stopped after the haptic interface guided the operator’s arm to the optimised configuration. The main advantage of the proposed method is that the human operator can perform the task with less effort, which increases the endurance time. To validate our approach, we performed proof-of-concept experiments on a teleoperation system composed of two Franka Emika robots, where one was serving as master and the other as slave.

[1]  David B. Kaber,et al.  Telepresence , 1998, Hum. Factors.

[2]  Manuel G. Catalano,et al.  Unifying bilateral teleoperation and tele-impedance for enhanced user experience , 2020, Int. J. Robotics Res..

[3]  R. Enoka,et al.  Muscle fatigue: what, why and how it influences muscle function , 2008, The Journal of physiology.

[4]  Tsung-Chi Lin,et al.  Physical Fatigue Analysis of Assistive Robot Teleoperation via Whole-body Motion Mapping , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[5]  Hamed Saeidi,et al.  Modeling and Control of Trust in Human and Robot Collaborative Manufacturing , 2014, AAAI Spring Symposia.

[6]  Dale A. Lawrence Stability and transparency in bilateral teleoperation , 1993, IEEE Trans. Robotics Autom..

[7]  Fouad Bennis,et al.  A new simple dynamic muscle fatigue model and its validation , 2022, ArXiv.

[8]  Tadej Petric,et al.  Human-in-the-loop approach for teaching robot assembly tasks using impedance control interface , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[9]  Jochen J. Steil,et al.  A User Study on Personalized Stiffness Control and Task Specificity in Physical Human–Robot Interaction , 2017, Front. Robot. AI.

[10]  Marcus G Pandy,et al.  A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement. , 2007, Journal of biomechanics.

[11]  M G Pandy,et al.  Static and dynamic optimization solutions for gait are practically equivalent. , 2001, Journal of biomechanics.

[12]  R. Berguer,et al.  Postural ergonomics during robotic and laparoscopic gastric bypass surgery: a pilot project , 2007, Journal of robotic surgery.

[13]  Nikolaos G. Tsagarakis,et al.  Anticipatory Robot Assistance for the Prevention of Human Static Joint Overloading in Human–Robot Collaboration , 2018, IEEE Robotics and Automation Letters.

[14]  Cheng Fang,et al.  A selective muscle fatigue management approach to ergonomic human-robot co-manipulation , 2019, Robotics Comput. Integr. Manuf..

[15]  Arash Ajoudani,et al.  Towards ergonomie control of human-robot co-manipulation and handover , 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).

[16]  Jun Morimoto,et al.  Assistive Arm-Exoskeleton Control Based on Human Muscular Manipulability , 2019, Front. Neurorobot..

[17]  Tadej Petric,et al.  Robotic assembly solution by human-in-the-loop teaching method based on real-time stiffness modulation , 2018, Auton. Robots.

[18]  C. D. De Luca,et al.  Myoelectrical manifestations of localized muscular fatigue in humans. , 1984, Critical reviews in biomedical engineering.

[19]  Scott L Delp,et al.  Generating dynamic simulations of movement using computed muscle control. , 2003, Journal of biomechanics.

[20]  Katherine J. Kuchenbecker,et al.  Induced Master Motion in Force-Reflecting Teleoperation , 2006 .

[21]  Manuel G. Catalano,et al.  Tele-impedance with force feedback under communication time delay , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[22]  Nikolaos G. Tsagarakis,et al.  Tele-impedance: Teleoperation with impedance regulation using a body–machine interface , 2012, Int. J. Robotics Res..

[23]  Nikolaos G. Tsagarakis,et al.  Robot adaptation to human physical fatigue in human–robot co-manipulation , 2018, Auton. Robots.

[24]  Walter Herzog,et al.  Model-based estimation of muscle forces exerted during movements. , 2007, Clinical biomechanics.

[25]  Oussama Khatib,et al.  Spanning large workspaces using small haptic devices , 2005, First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics Conference.