Robot's velocity optimization for planned path by hybrid adaptive dimensionality with GSO algorithm

Abstract

The robot velocity is one of the important factors to identify a mobile robot efficiency. This paper will present simple but efficient approach for controlling the robot's velocity in order to stabilize its movement when cornering and/or avoiding obstacles crush with suitable fast and safe navigation speed. In our previous work, we introduce a hybrid adaptive dimensionality with the Glowworm Swarm Optimization (GSO) algorithm approach to find an optimal path from initial point to the goal point. This will be extended in the current paper by using the path that was obtained by this approach to decide if the robot should change its velocity to avoid collision. Robot velocity controlling is an important in the following states. (1) When the robot navigates in the tight free area. (2) When the robot cornering around the angles of its path heading to its goal. This paper proposes an effective approach to robot velocity control that the robot selects the possible fastest velocity. To adopt this approach, two important factors must be taken into account to control the speed of robot in the above two cases, angle's value at each path's node as well as the number of obstacles that are surrounding this node which are located in the nearest two levels of this node toward the robot motion. The proposed approach successfully made the robot move around in its environments with adaptively controlling the velocity.