An adaptive manoeuvring strategy for mobile robots in cluttered dynamic environments

Abstract

A novel method which combines an optimised global path planner with a real-time sensor-based collision avoidance mechanism to accommodate for dynamic changes in the environment (e.g., people) is presented. The basic concept is to generate a continually changing parameterised family of virtual force fields for the robot based on characteristics such as location, travelling speed and dimension of the objects in the vicinity, static and dynamic. The interactions among the repulsive forces associated with the various obstacles provide a natural way for local collision avoidance in a partially known cluttered environment. This is harnessed by locally modifying the planned behaviour of the moving platform in real-time, whilst preserving the optimised nature of the global path. Furthermore, path traversability is continually monitored by the global planner to trigger a complete path re-planning from the current location in case of major changes, most notably when the path is completely blocked by obstacles.