LAUSR

Soft growing robots, a new soft mobile robot, have recently attracted considerable interest. There are many soft growing robots, some of which have irreversible growing and bending motion mechanisms. For such robots, path planning methods that provide information on bending timing improve operation efficiency. Although various path planning methods have already been developed, they cannot be applied to our growing robot that uses a heat welding mechanism because it has a constraint that all bending angles are the constant value. This letter proposes a novel path planning method with constant bending angle constraint. The proposed algorithm was developed based on the rapidly-exploring random tree star (RRT*) algorithm. The method incorporates an algorithm for reducing unnecessary nodes from obtained paths keeping bending angles constant and improving path optimality. We confirmed that the proposed method generates paths whose bending angles are constant. In addition, we experimented with moving our robot along the path in the field with some obstacles. The result showed that the proposed method enabled the robot to reach to target place, avoiding obstacles. The proposed method improves the operating efficiency of our soft growing robot.