It is difficult to find a practical solution for the backward-motion control of a car-like mobile robot with n passive trailers. Unlike an omni-directional robot, a car-like mobile robot has nonholonomic constraints and limitations of the steering angle. For these reasons, the backward motion control problem of a car-like mobile robot with n passive trailers is not trivial. In spite of difficulties, backing up a trailer system is useful for parking control. In this study, we proposed a mechanical alteration which is connecting n passive trailers to the front bumper of a car to improve the backward motion control performance. Theoretical verification and simulations show that the backward-motion control of a general car with n passive trailers can be successfully carried out by using the proposed approach.

We propose a formation-keeping and changing methods for outdoor multiple mobile robots in chained form. Our proposed method is designed to maintain the follower to its desired distance and orientation with respect to the pole using the concept of virtual force such as potential field. The client robots use a behavior-based control to perform kinematic control to keep formation under the centralized system in our software framework. The relationship of each poles that is expressed by set of distance and angle is the description of the formation type and the type converting is performed using this set. In addition, we also examine the stability and capability in the simulation and experiments with real robots.

The most important thing for navigation of a mobile robot is to find the most suitable path and avoid the obstacles in the static and dynamic environment. This paper presents a method to search the optimal path in start space extended to time domain with considering a velocity and a direction of moving obstacles. A modified version of A* algorithm has been applied for path planning in this work and proposed a method of path search to avoid a collision with moving obstacle in space-tim domain with a velocity and an orientation of obstacles. The velocity and the direction for moving obstacle are assumed as linear form. The simulation result shows that a mobile robot navigates safely among moving obstacles of constant linear velocity. This work can be applied for not only a moving robot but also a legged humanoid robot and all fields where the path planning is required.