Abstract:
Our goal is to establish a rigorous formulation for modeling the locomotion of a broad class of robotic systems. Recent research has identifi ed a number of systems with the structure of a principal fiber bundle. This framework has led to a number of tools for analysis and motion planning applicable to various robotic con gurations in different environments, but it also requires a number of assumptions that limit its usefulness to certain “idealized” systems. Systems that cannot be fully described with a principal fi ber bundle or cannot make full use of the subsequent tools include those whose joints are not fully controllable, those with control inputs or dynamics external to their mechanism, and those whose external con gurations do not form a symmetry group. In addition, the motion planning techniques derived from this structure have traditionally assumed a mapping from internal joint con gurations to external position con gurations. The reverse of this mapping will be discussed in this thesis, as well as the analysis and solutions for problems violating each of the above assumptions in turn. For each case, we introduce one or two motivating examples of robotic systems and discuss novel locomotive characteristics that do not previously appear under the standard assumptions. This thesis expands the applicability of the principal fiber bundle model, as well as derivative tools for analysis and motion planning, to a larger variety of locomoting systems.

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Thesis Committee Members:
Howie Choset, Chair
Matthew Travers
Scott Kelly, University of North Carolina at Charlotte
Koushil Sreenath, University of California, Berkeley