A probabilistic framework to monitor a multi-mode outdoor robot

Abstract

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented.

A Software component for simultaneous plan execution and adaptation

“…Before it can be executed, however, a specific MoveTo modality has 1 which are an adaptation of the transactions found in "classical" databases to be chosen. For example, our all-terrain rover has two motion modalities [7]. The NDD modality performs reactive obstacle avoidance by using a 2D laser range finder and can be used only on flat terrain.…”

A Framework for Simultaneous Plan Execution and Adaptation

“…Before it can be executed, however, a specific MoveTo modality has to be chosen. For example, our all-terrain rover has two motion modalities (Peynot and Lacroix, 2005) (Fig. 4).…”