Robot sweep path planning with weak field constrains under large motion disturbance

The sweeping robot plans a path and moves along its prior path. In conventional studies, the target field is separated into square cells to enable the robot to sweep evenly. The prior sweep path is generated by passing all the target cells. However, an outdoor sweeping robot cannot move as expected, because the robot cannot go to the next target easily due to the uncertainty of the motion of the robot. The uncertain motion is caused by individual differences of motors, disturbances from the environment, and position error. As a result, the robot passes the same point many times and the actual path length becomes longer. In this study, we propose sweep path planning to solve this problem by decreasing the number of cells that the robot must pass. Numerical simulations are carried out to verify our method and to verify the relation among the sweeping rate and robot disturbances. Simulation results show that our method is effective enabling the robot to satisfy a sweep rate of 80% and more, even if the robot has uncertainty of movement.