title: Towards using musculoskeletal models for intelligent control of physically assistive robots.
abstract: With the increasing number of robots being developed to physically assist humans in tasks such as rehabilitation and assistive living, more intelligent and personalized control systems are desired. In this paper we propose the use of a musculoskeletal model to estimate the strength of the user, from which information can be utilized to improve control schemes in which robots physically assist humans. An optimization model is developed utilizing a musculoskeletal model to estimate human strength in a specified dynamic state. Results of this optimization as well as methods of using it to observe muscle-based weaknesses in task space are presented. Lastly potential methods and problems in incorporating this model into a robot control system are discussed.
authors.affiliation: Centre for Autonomous Systems, Faculty of Engineering and IT, University of Technology Sydney, NSW 2007, Australia. marc.g.carmichael@eng.uts.edu.au
authors.forename: Marc G
authors.initials: MG
authors.lastname: Carmichael
authors.forename: Dikai
authors.initials: D
authors.lastname: Liu
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D008953:Models, Anatomic; D053580:Muscle Strength / Q000502:physiology; D009132:Muscles / Q000502:physiology; D009142:Musculoskeletal Physiological Phenomena; D012371:Robotics / Q000295:instrumentation*; D012656:Self-Help Devices