Predictive Models for Sensorimotor Control of Legged Locomotion
Abstract
We propose to develop generalizable tools for deriving and applying simple models that provide accurate quantitative predictions for dynamic locomotion and self-manipulation behaviors executed by robots and animals. We are motivated by questions targeting the analytical, computational, and experimental foundation of modeling dynamic sensorimotor control.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 05, 2019
- Accession Number
- AD1089549
Entities
People
- Samuel A. Burden
Organizations
- University of Washington