Using an augmentable resource to robustly and purposefully navigate a robot

Abstract

Presents a scheme for specifying and executing purposive navigation tasks for a behaviour-based mobile robot. A user specifies the robot's navigation task in general and qualitative terms using a graphical resource called the purposive map (PM). The robot navigates using the incomplete and approximate information stored in the PM as an aid to achieve the specified mission. The robot is able to augment the knowledge provided in the PM with environment information learnt by the robot. Using the augmented PM, the robot learns how to perform efficient obstacle avoidance. The authors present experimental results using a real robot to show their scheme is robust. The authors' robot can escape from dead-ends, can deduce that goals are unreachable and can withstand disturbances to the environment between missions.