Resolution-Exact Planner for a 2-link Planar Robot using Soft Predicates

Motion planning is a major topic in robotics. It frequently refers to motion of a robot in a R2 or R3 world that contains obstacles. Our goal is to produce algorithms that are practical and have strong theoretical guarantees. Recently, a new framework Soft Subdivision Search (SSS) was introduced to solve various motion planning problems. It is based on soft predicates and a new notion of correctness called resolution-exactness. Unlike most theoretical algorithms, such algorithms can be implemented without exact computation. In this thesis we describe a detailed, realized algorithm of SSS for a 2-link robot in R2. We prove the correctness of our predicates and also do experimental study of several strategies to enhance the basic SSS algorithm. In particular, we introduce a technique called T/R Splitting, in which the splittings of the rotational degrees of freedom are deferred to the end. The results give strong evidence of the practicability of SSS.