Design of a Helicopter Deployable Ground Robotic System for Hazardous Environments

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Virginia Tech

The use of robotics in hazardous environments is becoming more common, where autonomy can handle the dull, dirty and dangerous jobs that humans have previously supported. This thesis focuses on the design of a helicopter deployable unmanned ground vehicle for use in hazardous environments, and presents the benefits of heterogeneous unmanned vehicle teams for operation in beyond line-of-site hazardous environments.

The design of a ground robot that is capable of being flown on the undercarriage of a Yamaha RMAX unmanned air vehicle is presented. The robot is size, weight, and power limited and must be capable of traversing rough, unstructured terrain. The results of testing show that the design criteria for size, weight, and mobility are met. A path planning algorithm is developed using the A* search algorithm for the planning of optimal paths through rough terrain. The algorithm makes use of a vehicle/terrain interaction model to compute the cost of path traversal. In the CONOPS, the terrain model is generated real-time during a mission through the use of a stereovision system carried on the helicopter, which station-keeps above the ground robot. The algorithm simulates the robot on the terrain and presents the best feasible path to the operator to aid in teleoperated robot navigation. Simulations of the planning algorithm provided feasible paths over a rough terrain environment.

A user study was conducted that evaluates the abilities of both mono- and stereo-vision systems in providing the teleoperator with adequate situational awareness with the intent of proving that stereovision data is more effective at aiding the user in making timely navigation decisions. The results of the study showed that the helicopter-mounted stereovision system was more efficient than the monovision system with respect to navigation time, the number of invalid moves, and total moves required for navigation of a simulated rough terrain environment.

Robotics, Tracked Vehicle, Motion Planning, Teleoperation, Situational Awareness