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Publication Details

Reference TypeConference Proceedings
Author(s)Rotella, N.;Bloesch, M.;Righetti, L.;Schaal, S.
TitleState Estimation for Walking Humanoids on Unknown Terrain
Journal/Conference/Book TitleProceedings of Dynamic Walking 2014 (Poster)
Keywordshumanoid robotics, kalman filter, state estimation
AbstractState estimation plays a crucial role in humanoid locomotion;accurate estimates of the pose and velocity of the robot’s baseare necessary for walking tasks. Estimation in robotics haslong been focused on mobile robot localization, where wheelodometry and exteroceptive sensor data are fused to provideestimates of absolute position and yaw. While wheeled robotsare assumed to remain stable and in contact at all times,legged locomotion inherently involves intermittent contacts.This makes stability a concern and complicates odometrybasedapproaches, distinguishing estimation for legged systemsfrom that for wheeled robots. More recent approacheson quadruped and hexapod platforms make unreasonable assumptionsabout walking gaits, assume knowledge of the terrainand use exteroceptive sensor data for corrections. However,the utility of such platforms is their potential for operationin unstructured environments in which gaits are reactive,the terrain is unknown and such sensors are unfit for use. Motivatedby the task of providing robust and generic state estimationfor humanoid robots walking on unknown terrain, weintroduce an estimation framework [1] which employs onlyproprioceptive sensors and knowledge of leg kinematics.
Place PublishedZürich, Switzerland
Short TitleState Estimation for Walking Humanoids on Unknown Terrain
Custom 3papers3://publication/uuid/74AB703D-5C76-496C-8C73-C31F686F05AC
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