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Published October 26, 2022 | Version v1
Conference paper Open

Kinesthetic teaching of bi-manual tasks with known relative constraints

  • 1. Aristotle University Of Thessaloniki

Description

Kinesthetic teaching allows the direct skill transfer from the human to the robot and has been widely used to teach single arm tasks intuitively. In the bi-manual case, simultaneously moving both end-effectors is challenging due to the high physical and cognitive load imposed to the user. Thus, previous works on bi-manual task teaching resort to less intuitive methods by teaching each arm separately. This in turn requires motion synthesis and synchronization before execution. In this work, we leverage knowledge from the relative task space to facilitate a kinesthetic demonstration by guiding both end-effectors which is more human-like and intuitive
way for performing bi-manual tasks. Our method utilizes the notion of virtual fixtures and inertia minimization in the null space of the task. The controller is experimentally validated in a bi-manual task which involves the drawing of a preset line on a workpiece  utilizing two KUKA IIWA7 R800 robots. Results from ten participants were compared with a gravity compensation scheme  demonstrating improved performance

Files

Kinesthetic_teaching_of_bi_manual_tasks_with_known_relative_constraints.pdf

Additional details

Funding

BACCHUS – MoBile Robotic PlAtforms for ACtive InspeCtion and Harvesting in AgricUltural AreaS 871704
European Commission