Early User Appraisal of the MDARS Interior Robot
SPACE AND NAVAL WARFARE SYSTEMS CENTER SAN DIEGO CA
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The Mobile Detection Assessment Response System MDARS is a joint Army-Navy effort to field interior and exterior autonomous platforms for security and inventory assessment functions at DoD warehouses and storage sites. The MDARS operator interface host console is based upon the Multiple Resource Host Architecture MRHA, a distributed processing system that allows coordinated control of multiple autonomous resources. The current configuration provides control for up to 32 interior andor exterior robotic vehicles, with provision for near-term integration of remote fixed sensors or sensor pods. The MDARS-Interior MDARS-I effort, initiated in 1989 to improve the effectiveness of a shrinking guard force, was quickly expanded to address the intensive manpower requirements associated with accounting for high-dollar and critical assets. An integral component of the MRHA is the Product Assessment System, which extends the capabilities of MDARS into automated inventory management. The robotic platforms are equipped with an RF interrogator for reading interactive transponder tags attached to high-value or critical inventory items. Upon interrogation by the robot, individual tags respond with the stock number and any other relevant information concerning the product. The data collected is stored in a database for comparison with expected conditions, and any discrepancies subsequently flagged by geographic location for investigation. In 1995, a Broad Agency Announcement BAA contract was awarded to Cybermotion, Inc., of Roanoke, VA, to expand upon the government-developed interior prototype by adding improved navigation, extended intrusion detection, and RF interrogation of inventory. The upgraded platform passed formal Technical Feasibility Testing with flying colors in February 1997. This paper provides an overview of the MDARS-I robotic security system, some insights into the problems associated with installation, and a first assessment of lessons learned.
- Computer Hardware
- Miscellaneous Detection and Detectors