A famous viral video (watch below) about the DARPA Robotics Challenge shows all sorts of humanoid robots clumsily falling down. Bipedal movement is rather unstable, which is not only a problem for a robot trying to complete its task, but also because falling can damage a very expensive piece of machinery.
Roboticists across the globe are tackling this problem in a myriad of ways. While some look to add a series of corrective steps after a robot becomes off-balance, much like a person stumbling after tripping, Duke University’s Kris Hauser wants robots to be able to use the environment around them.
“如果一个人被推向墙壁或铁轨，他们将能够使用该表面使自己保持直立。我们希望机器人能够做同样的事情。“我们认为，我们是唯一一个研究机器人动态选择将其手放在哪里以防止下降的研究小组。”
而这样的决定和行动的第二天性to us, programming them into a robot’s reflexes is deceptively difficult. To streamline the process and save computation time, Hauser programs the software to focus only on the robot’s hip and shoulder joints. Hauser demonstrates this technique in the video above using a ROBOTIS Darwin Mini humanoid robot, Raspberry Pi 3 microcomputer, Adafruit BNO055 IMU and ROBOTIS TS-10 sensor.
As long as the robot isn’t twisting as it falls, this creates only three angles that the stabilization algorithm has to take into account—the foot to the hip, the hip to the shoulder, and the shoulder to the hand. The robot must identify nearby surfaces within reach and then quickly calculate the best combination of angles to catch itself.
The final solution minimizes impact when the robot’s hands make contact, and also minimizes the chance of its hands or feet slipping. The algorithm takes its best guess and then progressively optimizes it using a method called direct shooting. You can read more about this technique in the research paper “Realization of a Real-time Optimal Control Strategy to Stabilize a Falling Humanoid Robot with Hand Contact.”
秋季稳定后，机器人将保持稳定状态，可以等待被人搬迁以开始新步态，或者通过推开墙壁来恢复到直立的位置。这种方法使用肘部的弯曲运动，使机器人能够获得足够的动力来恢复站立的姿势。
在当前状态下，机器人有有关其环境供给它的信息，并且无法自行导航。但是，在不久的将来，豪瑟（Hauser）计划升级到具有自己的相机传感器的较大机器人，以使其看到周围的环境。
豪瑟说：“希望到年底，我们应该对机器人进行实验，实际上在现场障碍赛中工作。”“然后，我们将试图让机器人动态绘制周围的内容，以及如何保护自己免受任意环境的侵害。”
编者注：本文在允许的允许下重新发布杜克大学的普拉特工程学院。
提交以下：机器人报告，，，，机器人技术•机器人抓手•最终效应器
告诉我们你的想法！