Visual Collaboration Leader-Follower UAV-Formation for Indoor Exploration

Abstract

UAVs operating in a leader-follower formation demand the knowledge of the relative pose between the collaborating members. This necessitates the RF-communication of this information which increases the communication latency and can easily result in lost data packets. In this work, rather than relying on this autopilot data exchange, a visual scheme using passive markers is presented. Each formation-member carries passive markers in a RhOct configuration. These markers are visually detected and the relative pose of the members is on-board determined, thus eliminating the need for RF-communication. A reference path is then evaluated for each follower that tracks the leader and maintains a constant distance between the formation-members. Experimental studies show a mean position detection error (5 × 5 × 10cm) or less than 0.0031% of the available workspace [0.5 up to 5m, 50.43° × 38.75° Field of View (FoV)]. The efficiency of the suggested scheme against varying delays are examined in these studies, where it is shown that a delay up to 1.25s can be tolerated for the follower to track the leader as long as the latter one remains within its FoV.

A Leader-follower formation control of mobile robots by position-based visual servo method using fisheye camera

“…The realization of collision avoidance control is one of future issue to research. Furthermore, since a more robust position estimation of the leader is required to achieve reliable formation control, the multiple markers recognition such as Evageliou et al [17] is the future work, too.…”

Control Barrier Functions and Lidar-Inertial Odometry for Safe Drone Navigation in GNSS-denied Environments

“…Such solutions are however not applicable to navigation of purely unknown environments. In the case of multiple deployed agents, relative measurements have been used to guarantee formation control without external positioning [6], but the global planning problem remains unsolved.…”