Modeling and Control Techniques for a Class of Mobile Robot Error Recovery Problems

Abstract

A robot? locomotion mode fails when its environmental contacts fail, a situation called a locomotion error. For example, a legged robot cannot move when its leg becomes trapped in a crevice, and a wheeled robot is handicapped when its wheels skid. How can a robot recover when its standard locomotion mode fails? One way is to utilize any remaining freedoms to move the robot to a situation where the robot? standard locomotion mode is again feasible. However, planning and control for such unconventional motion is difficult, since the relationship between the robot? controls and its motion in a locomotion error is unclear. This complexity when combined with the uncertainty in environmental interaction (perceived as an ?lement of luck? in a locomotion error appears as a lack of structure, inducing operators to sometimes use random escape maneuvers. This thesis proposes finding recovery strategies by exploiting the structure inherent to the robot? constrained mobility and environmental interaction in the locomotion error. A robot equipped with multiple locomotion modes can choose between them depending on the circumstance, ultimately contributing to robust mobility. While robotic locomotion fails in many ways depending on the robot? design and the environmental interaction, this thesis finds novel recovery modes involving a combination of direct actuation and dynamically coupled actuation for two specific locomotion errors: first, a high-centered legged robot, where the robot? legs dangle in air; and second, a car trapped in a slippery pit. In the high-centered robot problem, we present a novel locomotion mode called ?egless locomotion? that allows the robot to locomote by rocking its body back and forth using leg swing without feedback about the robot? body motions. We use experiments and computer simulation to identify legless locomotion? properties and use simple models to derive an approximate control technique. In the car-in-ditch problem, we use computer simulation to find a control strategy involving wheel torques and an active-suspension that allows the car to roll out of the pit, while minimizing work done and perturbations to the car body. Finally, we present a classification structure for locomotion errors based on environmental influence.