Navigation-Assistant Path Planning within a MAV team

Abstract

In micro aerial vehicle (MAV) operations, the success of a mission is highly dependent on navigation performance, which has raised recent interests on navigation-aware path planning. One of the challenges lies in that optimal motions for successful navigation and the designated mission are often different in unknown, unstructured environments, and only sub-optimality may be obtained in each aspect. We aim to organize a two-MAV team that can effectively execute the mission and simultaneously guarantee navigation quality, which consists of a main-agent responsible for mission and a sub-agent for navigation of the team. Especially, this paper focuses on path planning of the sub-agent to provide navigational assistance to the main-agent using a monocular camera. We adopt a graph-based receding horizon planner to find a dynamically feasible path in order for the sub-agent to help the main-agent's navigation. In this process, we present a metric for evaluating the localization performance utilizing the distribution of the features projected to the image plane. We also design a map management strategy and pose-estimation support mechanism in a monocular camera setup, and validate their effectiveness in two scenarios.