Environmental Adaptability for Multi-Arm Multi-Flipper Disaster Response Robots

-Active Information Search in Real Space and Efficient Motion Search in Virtual Space-

Abstract

In this study, we develop an environment adaptability enhancement system with active information search in real space and high efficiency motion search in virtual space for multi-degree of freedom disaster response robot. For such robots to work safely, estimating the work achievability before executing it is important. However, in disaster sites, failed motions such as falls increase the risk of secondary disasters, so it is difficult to learn motions by trial and error. Thus, the robot obtains the environment information in real space and reproduces them in virtual space, and then performs motion search efficiently in virtual space. Due to the limitation of the reproduction accuracy, for finer adjustment, the robot performs active touches to acquire ground properties such as friction and hardness in real space. The experimental results showed that the proposed system could judge work availability by trying robot motions and provide the robot with efficient motions.