抄録
In this article, an extended Kalman filter based estimation method is proposed for positional relationships between a vehicle and robots for a car transportation system using two robots. This system lifts only the two front wheels of a front wheel drive vehicle, which is commonly used and cannot move automatically, and positions it. Therefore, the system can be made more compact than previous car transportation systems using multiple robots. To control the system transporting cars, some parameters related to positional relationships between robots and a car's nonholonomic constraints are required. However, it is difficult to obtain accurate positional relationships using laser range scanners because the car's body is complexly curved and hides one robot from another.
This estimation method uses force sensors and encoders on robots instead of laser range scanners. A force based cooperative transportation control enables the system to transport cars with nonholonomic constraints without positional relationships. The positional relationships between the robots and conditions of a car's nonholonomic constraints are derived by the extended Kalman filter and a state space model relating robotic motions and positional relationships.
