Affiliation:
1. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA 02139, USA,
2. Ascending Technologies GmbH, Graspergerstrasse 8, 82131 Stockdorf, Germany,
Abstract
The MAV ’08 competition focused on the problem of using air and ground vehicles to locate and rescue hostages being held in a remote building. To execute this mission, a number of technical challenges were addressed, including designing the micro air vehicle (MAV), using the MAV to geo-locate ground targets, and planning the motion of ground vehicles to reach the hostage location without detection. In this paper, we describe the complete system designed for the MAV ’08 competition, and present our solutions to three technical challenges that were addressed within this system. First, we summarize the design of our MAV, focusing on the navigation and sensing payload. Second, we describe the vision and state estimation algorithms used to track ground features, including stationary obstacles and moving adversaries, from a sequence of images collected by the MAV. Third, we describe the planning algorithm used to generate motion plans for the ground vehicles to approach the hostage building undetected by adversaries; these adversaries are tracked by the MAV from the air. We examine different variants of a search algorithm and describe their performance under different conditions. Finally, we provide results of our system’s performance during the mission execution.
Subject
Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software
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2. Bertsekas, Dimitri P. ( 2005). Dynamic programming and optimal control, Vol 1, 3rd Edition. Belmont, MA: Athena Scientific. pp 300-303.
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