Many applications require robots to move through terrain with large obstacles, such as self-driving, search and rescue, and extraterrestrial exploration. Although robots are already excellent at avoiding sparse obstacles, they still struggle in traversing cluttered obstacles. Inspired by cockroaches that use and respond to physical interaction with obstacles in various ways to traverse grass-like beams with different stiffness, here we developed a physics model of a minimalistic robot capable of environmental force sensing propelled forward to traverse two beams to simulate and understand the traversal of cluttered obstacles. Beam properties like stiffness and deflection locations could be estimated from the noisy beam contact forces measured, whose fidelity increased with sensing time. Using these estimates, the model predicted the cost of traversal defined using potential energy barriers and used it to plan and control the robot to generate and track a trajectory to traverse with minimal cost. When encountering stiff beams, the simulation robot transitioned from a more costly pitch mode to a less costly roll mode to traverse. When encountering flimsy beams, it chose to push cross beams with less energy cost than avoiding beams. Finally, we developed a physical robot and demonstrated the usefulness of the estimation method.
翻译:许多应用都要求机器人在具有巨大障碍的地形中移动,例如自驾驶、搜索和救援以及外星探索。虽然机器人在避免稀少的障碍方面已经非常出色,但它们仍然在艰难的障碍中挣扎。受使用和应对物理互动障碍的蟑螂的启发,这些蟑螂以各种方式利用和应对物理互动,以不同僵硬的方式穿过草样的横梁,在这里,我们开发了一个最微小的机器人物理学模型,能够对环境力感应进行微小的机器人,推向两条横梁,模拟和理解断层障碍的曲折。在测量的噪音波束接触力中,可以估计僵硬和偏转位置等波形特性,这些特性随着感测时间的增加而提高。模型预测了使用潜在能源屏障来界定的曲道的成本,并用它来规划和控制机器人以最低成本生成和跟踪曲流的轨道。在遇到僵硬的波束时,模拟机器人从更昂贵的投球模式转换成一个费用较低的滚动模式。在遇到飞跃时,会遇到僵硬的波波状时,我们选择以低于实际用途的方法来回避。最后显示,我们避免成本。