Collaborative air-ground target searching in complex environments

Abstract

Collaboration between heterogeneous robots can greatly improve the overall robot system by obtaining capabilities that each single robot is unable to achieve. In this paper, we present a collaborative robot system designed for search and rescue missions in an unknown environment with obstacles. The system consists of an aerial robot and a ground robot. An extended Kalman filter (EKF) is used for robot pose estimation, and an online trajectory generation algorithm is implemented for dynamic obstacle avoidance of the ground robot. The aerial robot first surveys an area of interests and sources a number of targets. The ground robot is then guided by the aerial robot to reach the target location while at the same time avoids obstacles along the way using a laser range finder. The system is entirely autonomous, achieves maximum efficiency and releases the human operator from all low-level types of operations. A centralized EKF is implemented with the flexibility of easily being modified into a distributed EKF.