title: Optimizing Locomotion Controllers Using Biologically-Based Actuators and Objectives.
abstract: We present a technique for automatically synthesizing walking and running controllers for physically-simulated 3D humanoid characters. The sagittal hip, knee, and ankle degrees-of-freedom are actuated using a set of eight Hill-type musculotendon models in each leg, with biologically-motivated control laws. The parameters of these control laws are set by an optimization procedure that satisfies a number of locomotion task terms while minimizing a biological model of metabolic energy expenditure. We show that the use of biologically-based actuators and objectives measurably increases the realism of gaits generated by locomotion controllers that operate without the use of motion capture data, and that metabolic energy expenditure provides a simple and unifying measurement of effort that can be used for both walking and running control optimization.
authors.affiliation: Stanford University.
authors.forename: Jack M
authors.initials: JM
authors.lastname: Wang
authors.affiliation: Stanford University.
authors.forename: Samuel R
authors.initials: SR
authors.lastname: Hamner
authors.affiliation: Stanford University.
authors.forename: Scott L
authors.initials: SL
authors.lastname: Delp
authors.affiliation: Stanford University.
authors.forename: Vladlen
authors.initials: V
authors.lastname: Koltun
keywords: biomechanics; musculoskeletal simulation; physics-based character animation