cognitive robotics, navigation, sensory fusion
Computer Engineering | Robotics
We consider the scenario where an autonomous platform that is searching or traversing a building may observe unstable masonry or may need to travel over unstable rubble. A purely behaviour-based system may handle these challenges but produce behaviour that works against long-terms goals such as reaching a victim as quickly as possible. We extend our work on ADAPT, a cognitive robotics architecture that incorporates 3D simulation and image fusion, to allow the robot to predict the behaviour of physical phenomena, such as falling masonry, and take actions consonant with long-term goals.
We experimentally evaluate a cognitive only and reactive only approach to traversing a building filled with various numbers of challenges and compare their performance. The reactive only approach succeeds only 38% of the time, while the cognitive only approach succeeds 100% of the time. While the cognitive only approach produces very impressive behaviour, our results indicate how much better the combination of cognitive and behaviour-based can be.
Lyons, Damian M.; Nirmal, Prem; and Benjamin, D. Paul, "Navigation of Uncertain Terrain by Fusion of Information from Real and Synthetic Imagery" (2012). Faculty Publications. 4.
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications at the SPIE Defense and Security Symposium, Baltimore MD, April 2012.
This research was conducted at the Fordham University Robotics and Computer Vision Lab. For more information about graduate programs in Computer Science, see http://www.cis.fordham.edu/graduate.html, and the Fordham University Graduate School of Arts and Sciences, see http://www.fordham.edu/gsas.