An efficient strategy for robot navigation in cluttered environments in the presence of dynamic obstacles

Abstract

A novel method which combines an optimised global path planner with real-time sensor-based collision avoidance capabilities in order to avoid moving obstacles (e.g. people) in a complex environment is presented. The strategy is based on a time efficient one step path planning algorithm for navigating a large robotic platform in indoor environments. The planner, which has been proved to compare favourably to currently available path planning algorithms such as Randomly-exploring Random Trees (RRTs) and Probabilistic Road Maps (PRMs) in known static conditions, is enhanced here with a modified Variable Speed Force Field (V SF 2 ) mechanism to accommodate for dynamic changes of the environment. The basic concept of the modified DV SF 2 is to generate a continually changing parameterised familiy of virtual force fields for the robot based on characteristics such as location, travelling speed, heading and dimension of all the objects present 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 and situational awareness. This is harnessed here by locally modifying the planned behaviour of the moving platform in real time, whilst preserving as much as possible the optimised nature of the global path. Furthermore, traversability of the path is continually monitored by the global planner to trigger a complete re-planning from the robot's current location in the case of major changes to the environment, most notably when the path is completely blocked by an obstacle. Overall, a complete solution to the navigational problem in partially known cluttered environments is provided. I. MOTIVATION