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Autonomous car driving by a humanoid robot

机译:人形机器人的无人驾驶汽车

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摘要

Enabling a humanoid robot to drive a car, requires the development of a set of basic primitive actions. These include: walking to the vehicle, manually controlling its commands (e.g., ignition, gas pedal and steering), and moving with the whole-body, to ingress/egress the car. In this paper, we present a sensor-based reactive framework for realizing the central part of the complete task, consisting in driving the car along unknown roads. The proposed framework provides three driving strategies by which a human supervisor can teleoperate the car, ask for assistive driving, or give the robot full control of the car. A visual servoing scheme uses features of the road image to provide the reference angle for the steering wheel to drive the car at the center of the road. Simultaneously , a Kalman filter merges optical flow and accelerometer measurements, to estimate the car linear velocity and correspondingly compute the gas pedal command for driving at a desired speed. The steering wheel and gas pedal reference are sent to the robot control to achieve the driving task with the hu-manoid. We present results from a driving experience with a real car and the humanoid robot HRP-2Kai. Part of the framework has been used to perform the driving task at the DARPA Robotics Challenge.
机译:要使人形机器人驾驶汽车,就需要开发一组基本的原始动作。其中包括:步行至车辆,手动控制其命令(例如点火,油门踏板和转向)以及全身移动以使车辆进入/驶出。在本文中,我们提出了一种基于传感器的反应性框架,用于实现整个任务的核心部分,包括沿着未知的道路驾驶汽车。提议的框架提供了三种驾驶策略,人类主管可以通过这些策略遥控汽车,请求辅助驾驶或让机器人完全控制汽车。视觉伺服方案利用道路图像的特征为方向盘提供参考角度,以在道路中心驾驶汽车。同时,卡尔曼滤波器将光流和加速度计的测量结果合并在一起,以估算汽车的线速度,并相应地计算出用于以所需速度行驶的油门踏板命令。方向盘和油门踏板参考被发送到机器人控制装置,以实现人形机器人的驾驶任务。我们展示了真实汽车和人形机器人HRP-2Kai的驾驶经验。在DARPA机器人挑战赛上,部分框架已用于执行驾驶任务。

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