A new on-line real-time approach with obstacle avoidance for mobile robots moving in an uncertain environment has been proposed and implemented. With the integration of global planning and local planning, this path planning approach is based on polar coordinates in which the desirable direction angle is taken into consideration as an optimization index. Detecting unknown obstacles with local feedback information by robot's sensor system, this approach orients the desirable direction of mobile robot so as to generate local sub-goal in every planning window. As a result, the difference between real direction angle and desirable direction angle of robot motion steers the mobile robot to detour collisions and advance toward the target without stopping to re-plan a path when new sensor data become available. This approach is not only simple and flexible, but also overcomes flaws of global planning and local planning. The effectiveness, feasibility, real-time performance, optimization capability, high precision and perfect stability are demonstrated by means of simulation examples.

A B S T R A C TWe propose a novel and efficient scheme to plan a kinematically feasible path in the presence of obstacles according to task requirements. By employing a geometrical analysis, expressions can be derived to describe the relationship between the planned path, kinematic constraints, and obstacles in the robot workspace. The freedom available according to task requirements is then utilized to modify the infeasible portions of the planned path. To demonstrate the proposed scheme, a 6R (revolute) wrist-partitioned type of robot manipulator and a spherical obstacle are used as a case study. The results are then extended to general wrist-partitioned types of robot manipulators, and arbitrarily-shaped or multiple obstacles.