Task-aware waypoint sampling for robotic planning
Keren, Sarah and Canal, Gerard and Cashmore, Michael; (2021) Task-aware waypoint sampling for robotic planning. In: Proceedings of the International Conference on Automated Planning and Scheduling. AAAI Press, CHN, pp. 643-651. (https://ojs.aaai.org/index.php/ICAPS/article/view/...)
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Abstract
To achieve a complex task, a robot often needs to navigate in a physical space to complete activities in different locations. For example, it may need to inspect several structures, making multiple observations of each structure from different perspectives. Typically, the positions from which these activities can be performed are represented as waypoints – discrete positions that are sampled from the continuous physical space and used to find a task plan. Existing approaches to waypoint selection either iteratively consider the entire space or use domain knowledge to consider each activity separately. This can lead to task planning problems that are more complex than is necessary or to plans of compromised quality. Moreover, all previous approaches only consider geometric constraints that can be imposed on the waypoint selection process. We present Task-Aware Waypoint Sampling (TAWS), which offers two key novelties. First, it is an anytime approach that combines the benefits of random sampling with the use of domain knowledge in waypoint selection by performing a onetime computation of the connectivity graph from which waypoints are sampled. In addition, TAWS is the first approach that accounts for performance preferences, which are preferences a system operator may have about the generated task plan. These can account, for example, for areas near doorways where it is preferable that the robot does not stop to perform activities. We demonstrate the performance benefits of our approach on simulated automated manufacturing tasks.
ORCID iDs
Keren, Sarah, Canal, Gerard and Cashmore, Michael ORCID: https://orcid.org/0000-0002-8334-4348;-
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Item type: Book Section ID code: 77086 Dates: DateEvent13 August 2021Published13 August 2021Published Online16 February 2021AcceptedSubjects: Technology
Science > Mathematics > Electronic computers. Computer scienceDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 14 Jul 2021 12:36 Last modified: 22 Sep 2024 00:39 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/77086