Reviews: Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs

Overview and Summary This paper presents a method for motion planning where the cost of evaluating transitions between robot configurations is high. The problem is formulated as a graph-search algorithm, where the order of graph expansion has a large impact on the performance of the algorithm due to the edge expansion cost. The paper uses ideas from optimal test selection in order to derive the resulting algorithm. The algorithm is tested on a number of synthetic datasets, a simulator, and a real-world helicopter planning problem. Detailed Comments This paper extended work within the well-studied domain of robotic motion planning, extending and combining prior work in the area to construct a new algorithm.