Soft and Bio-Inspired Legged Locomotion for Climbing in Extreme Environments

主要目标将是开发一种有腿的机器人，它可以使用柔软的仿生部件在极端环境中攀爬。轮式机器人只能在达到一定倾斜度之前使用，无人机只能在非常有限的时间内使用，而腿式机器人甚至可以穿越困难的地形。使用软体和仿生组件的目标是降低控制复杂性和生产这种机器人的成本。这里选择的示例环境是火山，需要在其中进行长期测量。与火山学家Emma Liu博士（UCL）的讨论已经确定了自主地面机器人的潜力，可以为大大改善现场火山测量提供平台。火山是一个危险的环境，这使得人类无法进行测量，而且由于特殊的拓扑结构，轮式机器人难以进入。最后，无人机的使用也只能在有限的程度上，因为测量必须在更长的时间框架内进行。正因为如此，这对有腿的爬行机器人来说是一个完美的场景。虽然存在不同的腿式机器人系统，专门用于在极端环境中攀爬，但它们制造复杂且成本高昂，因此尚未在相关的现实环境中使用。通过创造一个软腿机器人，单个机器人的成本可以大大降低，由于更便宜的材料，如硅，以及通过减少传感器的使用和计算能力，由于软机器人的体现智能。

The main goal will be to develop a legged robot, which can climb in extreme environments using soft and bio-inspired components. While wheeled robots can only be used until a certain inclination is reached anddrones only for a very limited time, legged robots can traverse even difficult terrains. The goal in using soft and bio-inspired components is to decrease the control complexity and the cost of producing such robots.The example environment chosen here is a volcano, in which long term measurements need to be made.Discussions with volcanologist Dr Emma Liu (UCL) have identified the potential for autonomous terrestrial robots to provide a platform for greatly improved volcano measurements in the field. The volcano is a dangerous environment, which makes it impractical for humans to conduct measurements, but also an environment which is difficult for wheeled robots to move in due to the special topology. Lastly, the use of UAVs is also only possible to a limited degree, as the measurements must be taken over a longer time frame. Because of this, this is a perfect scenario for legged climbing robots.While different legged robot systems exist, specifically for climbing in extreme environment, they are complex and expensive to manufacture, and as such are yet to be used in related real-world environments. By creating a soft legged robot, the cost of a single robot can be drastically reduced, due to cheaper materials such as silicone as well as through the reduced of use of sensors and computational power thanks to the embodied intelligence of soft robots.