Path-Constrained Haptic Motion Guidance via Adaptive Phase-Based Admittance Control (Abstract Reprint)

Robots have surpassed humans in terms of strength and precision, yet humans retain an unparalleled ability for decision-making in the face of unpredictable disturbances. This article aims to combine the strengths of both entities within a singular task: human motion guidance under strict geometric constraints, particularly adhering to predetermined paths. To tackle this challenge, a modular haptic guidance law is proposed that takes the human-applied wrench as an input. Using an auxiliary variable called phase, the generated desired motion is guaranteed to consistently adhere to the constraint path. The guidance policy can be generalized into physically interpretable terms, adjustable either prior to initiating the task or dynamically while the task is in progress. An illustrative guidance adaptation policy is showcased that takes into account the human's manipulability. Passivity analysis is used to ensure overall system stability. Experiments, including a 20-participant user study, explore various aspects of the approach in practice.

Authors

• Erfan Shahriari Robotics and Systems Intelligence, Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany Newman Laboratory for Biomechanics and Human Rehabilitation, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
• Petr Svarny Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
• Seyed Ali Baradaran Birjandi Robotics and Systems Intelligence, Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany
• Matej Hoffmann Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
• Sami Haddadin Robotics and Systems Intelligence, Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE

Keywords

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