In this work we tackle the path planning problem for a 21-dimensional snake robot-like manipulator, navigating a cluttered gas turbine for the purposes of inspection. Heuristic search-based approaches are effective planning strategies for common manipulation domains. However, their performance on high dimensional systems is heavily reliant on the effectiveness of... [Read More]

Heuristic-based graph search algorithms like A* are frequently used to solve motion planning problems in many domains. For most practical applications, it is infeasible and unnecessary to pre-compute the graph representing the whole search space. Instead, these algorithms generate the graph incrementally by applying a fixed set of actions (frequently... [Read More]

This work presents a method for motion planning under uncertainity to deal with situations where ambiguous data associations result in a multi-modal hypothesis on the robot state. We present an approach, to plan actions that sequentially disambiguate a multimodal belief to achieve a unimodal belief in finite amount of time.... [Read More]