Competition

MyoChallenge 2023: Towards Human-Level Dexterity and Agility

Vittorio Caggiano · · Guillaume Durandau · Seungmoon Song · Cameron Berg · Pierre Schumacher · Chun Kwang Tan · Massimo Sartori · Vikash Kumar

Room 354
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Sat 16 Dec 7 a.m. PST — 10 a.m. PST

Abstract:

Humans effortlessly grasp objects of diverse shapes and properties and execute agile locomotion without overwhelming their cognitive capacities. This ability was acquired through millions of years of evolution, which honed the symbiotic relationship between the central and peripheral nervous systems and the musculoskeletal structure. Consequently, it is not surprising that uncovering the intricacies of these complex, evolved systems underlying human movement remains a formidable challenge. Advancements in neuromechanical simulations and data driven methods offer promising avenues to overcome these obstacles. To this end, we propose to organize \longName, where we will provide a highly detailed neuromechanical simulation environment and invite experts to develop any type of controller, including state-of-the-art reinforcement learning. Building on the success of NeurIPS 2022: MyoChallenge, which focused on manipulating single objects with a highly articulated musculoskeletal hand, this year's competition will feature two tracks: the manipulation track and the locomotion track. The manipulation track will utilize a substantially extended musculoskeletal model of the hand with added elbow and shoulder, MyoArm, which has 27 DOFs controlled by 63 muscles, and aims to realize generalizable manipulation for unseen objects. The new locomotion track will feature the newly developed MyoLeg, which represents the full body with articulated legs featuring 16 DOFs controlled by 80 muscles. This track aims to push the boundaries of agile locomotion and benchmark the World Chase Tag match. The competition is not only suitable for testing state-of-the-art reinforcement learning techniques but will also advance our understanding of human movement toward improved rehabilitation and assistive technologies.

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