Paper
23 May 2011 Lessons from risk assessment of countermine robotic systems
Isaac Chappell, Franklin L. Moses, Matthew P. Aeillo
Author Affiliations +
Abstract
The U.S. Army's desire for increased standoff distances between Soldiers and disguised explosive threats has yielded a complex new technical challenge: augment existing small military robots with state-of-the-art detection and neutralization technology. The magnitude of the challenge is increased by the need for reliable autonomy that allows the robot to operate in different environments (e.g., complex and urban terrains, confined areas, and underground locations). This paper describes lessons learned during efforts in 2008-09 to identify and remediate risks of developing a countermine robot system. It also addresses issues that need attention to achieve total mission success. The work studied three phases of a robotic countermine system: move to a threat area, investigate that area with sensor(s), and neutralize detected threats. Each of these phases is essential, yet attention tends to focus on the third one. The focus of this paper is on risks and lessons pertaining to the first two. What was learned about moving a countermine robot to the area of expected threats? What is necessary for a robot to maneuver sensors and have the maximum probability of detection (Pd) of hazards while minimizing the false alarm rate (FAR)? This paper presents observations during demonstration and test events over the past 2 years. From those observations, lessons learned are summarized as a foundation for realizing a countermine robot and a path forward.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Isaac Chappell, Franklin L. Moses, and Matthew P. Aeillo "Lessons from risk assessment of countermine robotic systems", Proc. SPIE 8045, Unmanned Systems Technology XIII, 80450Q (23 May 2011); https://doi.org/10.1117/12.886490
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KEYWORDS
Robots

Sensors

Control systems

Robotic systems

Navigation systems

Robotics

Curium

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