CMU RI Defense: Modeling and Control Techniques for a Class of Mobile Robot Error Recovery Problems

Ravi Balasubramanian, Robotics Institute, Carnegie Mellon University
24 Jul 2006

Abstract: A robot's 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's standard locomotion mode is again feasible. However, such unconventional motion is difficult, since the relationship between the robot's controls and its motion in a locomotion error is unclear. The uncertainty and the perceived "element of luck" in locomotion error recovery appears as a lack of structure, inducing operators to sometimes use random maneuvers which can worsen the predicament. This thesis proposes finding recovery strategies by exploiting the structure inherent to the robot's constrained mobility and environmental interaction in the locomotion error. A robot equipped with multiple locomotion modes, even some inefficient modes, can choose between them depending on the circumstances, ultimately contributing to robust mobility.

While robotic locomotion fails in many ways depending on the robot's 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's body is stuck on a rock and the robot's 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 ``legless locomotion'', that allows the robot to locomote simply by rocking its body back and forth using leg swing without feedback about the robot's body motions. We use experiments and computer simulation to identify legless locomotion's key elements and use simple models to derive an approximate control technique. In the stuck-car 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 the work done and the perturbations to the car body and satisfying the contact constraints. Finally, we present a classification structure for locomotion errors based on environmental influence.

Further Details: A copy of the thesis oral document can be found at http://www.cs.cmu.edu/~bravi/thesis.pdf.