Integration of Symbolic Task Planning into Operations within an Unstructured Environment

Integration of Symbolic Task Planning into Operations within an Unstructured Environment

Renxi Qiu (Cardiff University, UK), Alexandre Noyvirt (Cardiff University, UK), Ze Ji (Cardiff University, UK), Anthony Soroka (Cardiff University, UK), Dayou Li (University of Bedfordshire, UK), Beisheng Liu (University of Bedfordshire, UK), Georg Arbeiter (Fraunhofer IPA, Germany), Florian Weisshardt (Fraunhofer IPA, Germany) and Shuo Xu (Shanghai University, China)
Copyright: © 2012 |Pages: 20
DOI: 10.4018/ijimr.2012070104
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To ensure a robot capable of robust task execution in unstructured environments, task planners need to have a high-level understanding of the nature of the world, reasoning for deliberate actions, and reacting to environment changes. Proposed is a practical task planning approach that seamlessly integrating deeper domain knowledge, real time perception and symbolic planning for robot operation. A higher degree of autonomy under unstructured environment will be endowed to the robot with the proposed approach.
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A classical approach of task planning is to build complex robot behaviours based on hierarchal structure (Nakamura, Hanafusa, & Yoshikawa, 1987; Mansard & Chaumette, 2007). In literatures, different ways to define hierarchy among the tasks have been explored. In Decre, Smits, Bruyninckx, and De Schutter (2009), the priority between the tasks is defined by weighting the influence of each task with respect to the others. In Escande, Mansard, and Wieber (2010) and Siciliano and Slotine (1991) a stack-of-task mechanism is defined, where the priority between the tasks is ensured by realizing each task in the null space left by tasks of higher priority.

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