Achievement of recognition guided teleoperation driving system for humanoid robots with vehicle path estimation

In the wake of the DARPA Robotics Challenge, the task for robots to drive vehicles has been expected to be a method for robots to transport themselves to the disaster site where it is hazardous for humans to approach. In the driving task, it is important for the robot to estimate the path of the vehicle and select an appropriate path for navigation through unknown obstacles, even under limited communication with an operator. It is also necessary for robots to suggest the estimated path of vehicle to an operator to deal with unforeseen circumstances. Therefore, we propose a recognition guided teleoperated driving system for robots to drive vehicles in disaster sites with estimated vehicle path based on steering angle and vehicle model. First, we show model based steering and pedaling strategy to achieve the target steering angle for desired path. Next, we propose a vehicle path estimation and a local planner that can suggest a traveling path according to the surroundings. We integrated them into a teleoperation system for bandwidth limited environments as recognition guidance. Finally, we show the effectiveness of our driving system by conducting field driving experiments with three different robots: JAXON, STARO and HRP-2.