Integrating perception and problem solving to predict complex object behaviors

Damian M. Lyons; Sirhan Chaudhry; Marius Agica; John Vincent Monaco

doi:10.1117/12.852484

28 April 2010 Integrating perception and problem solving to predict complex object behaviours

Damian M. Lyons, Sirhan Chaudhry, Marius Agica, John Vincent Monaco

Proceedings Volume 7710, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010; 77100G (2010) https://doi.org/10.1117/12.852484
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

One of the objectives of Cognitive Robotics is to construct robot systems that can be directed to achieve realworld goals by high-level directions rather than complex, low-level robot programming. Such a system must have the ability to represent, problem-solve and learn about its environment as well as communicate with other agents. In previous work, we have proposed ADAPT, a Cognitive Architecture that views perception as top-down and goaloriented and part of the problem solving process. Our approach is linked to a SOAR-based problem-solving and learning framework. In this paper, we present an architecture for the perceptive and world modelling components of ADAPT and report on experimental results using this architecture to predict complex object behaviour. A novel aspect of our approach is a 'mirror system' that ensures that the modelled background and foreground objects are synchronized with observations and task-based expectations. This is based on our prior work on comparing real and synthetic images. We show results for a moving object that collides and rebounds from its environment, hence showing that this perception-based problem solving approach has the potential to be used to predict complex object motions.

Citation Download Citation

Damian M. Lyons, Sirhan Chaudhry, Marius Agica, and John Vincent Monaco "Integrating perception and problem solving to predict complex object behaviours", Proc. SPIE 7710, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010, 77100G (28 April 2010); https://doi.org/10.1117/12.852484

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