Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Air Force Research Laboratory, Information Directorate, Rome, NY 13441, USA.
Sci Robot. 2020 Oct 21;5(47). doi: 10.1126/scirobotics.abb6938.
Algorithms for mobile robotic systems are generally implemented on purely digital computing platforms. Developing alternative computational platforms may lead to more energy-efficient and responsive mobile robotics. Here, we report a hybrid analog-digital computing platform enabled by memristors on a mobile inverted pendulum robot. Our mobile robotic system can tune the conductance states of memristors adaptively using a model-free optimization method to achieve optimal control performance. We implement sensor fusion and the motion control algorithms on our hybrid analog-digital computing platform and demonstrate more than one order of magnitude enhancement of speed and energy efficiency over traditional digital platforms.
移动机器人系统的算法通常在纯数字计算平台上实现。开发替代的计算平台可能会导致更节能和响应更迅速的移动机器人。在这里，我们报告了一种基于忆阻器的混合模拟-数字计算平台，该平台在移动倒立摆机器人上得以实现。我们的移动机器人系统可以使用无模型优化方法自适应地调整忆阻器的电导状态，以实现最佳的控制性能。我们在混合模拟-数字计算平台上实现了传感器融合和运动控制算法，并展示了比传统数字平台快一个数量级以上的速度和节能效率提升。
