Structured around ideas from computational geometry and robotics, this work shows how to model constraints, connect placements, and solve the online planning problem step by step. It blends theory with practical algorithm ideas, including how to extend a roadmap with jumps and how to measure algorithm performance.

How the roadmap of feasible placements is built and why it stays connected.
The concept of jumps or pseudo arcs that extend the network in meaningful ways.
What a normalized problem is and how solving it helps tackle the general motion planning task.
How complexity and efficiency are analyzed, with guidance on implementing the ideas.

Ideal for readers interested in robotics, motion planning, and computational geometry who want a rigorous yet approachable treatment.

About the Author

JAMES H. COX is Assistant Professor, Department of Government, California State University, Sacramento.

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