Cooperative human-robot search in a partially-known environment using multiple UAVs
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This thesis details out a system developed with objective of conducting cooperative search operation in a partially-known environment, with a human operator, and two Unmanned Aerial Vehicles (UAVs) with nadir, and front on-board cameras. The system uses two phases of flight operations, where the first phase is aimed at gathering latest overhead images of the environment using a UAV’s nadir camera. These images are used to generate and update representations of the environment including 3D reconstruction, mosaic image, occupancy image, and a network graph. During the second phase of flight operations, a human operator marks multiple areas of interest for closer inspection on the mosaic generated in previous step, displayed via a UI. These areas are used by the path planner as visitation goals. The two-step path planner, which uses network graph, utilizes the weighted-A* planning, and Travelling Salesman Problem’s solution to compute an optimal visitation plan. This visitation plan is then converted into Mission waypoints for a second UAV, and are communicated through a navigation module over a MavLink connection. A UAV flying at low altitude, executes the mission plan, and streams a live video from its front-facing camera to a ground station over a wireless network. The human operator views the video on the ground station, and uses it to locate the target object, culminating the mission.
General Audience Abstract
This thesis details out the work focused on developing a system capable of conducting search operation in an environment where prior information has been rendered outdated, while allowing human operator, and multiple robots to cooperate for the search. The system operation is divided into two phases of flight operations, where the first operation focuses on gathering the current information using a camera equipped unmanned aircraft, while the second phase involves utilizing the human operator’s instinct to select areas of interest for a close inspection. It is followed by a flight operation using a second unmanned aircraft aimed at visiting the selected areas and gathering detailed information. The system utilizes the data acquired through first phase, and generates a detailed map of the target environment. In the second phase of flight operations, a human uses the detailed map, and marks the areas of interest by drawing over the map. This allows the human operator to guide the search operation. The path planner generates an optimal plan of visitation which is executed by the second unmanned aircraft. The aircraft streams a live video to a ground station over a wireless network, which is used by the human operator for detecting the target object’s location, concluding the search operation.
- Masters Theses