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| Content Provider | Springer Nature Link |
|---|---|
| Author | Mokhtari, Vahid Seabra Lopes, Luís Pinho, Armando J. |
| Copyright Year | 2016 |
| Abstract | Deliberation and learning are required to endow a robot with the capabilities for acquiring knowledge, performing a variety of tasks and interactions, and adapting to open-ended environments. This paper presents the notion of experience-based planning domains (EBPDs) for task level learning and planning in robotics. EBPDs provide methods for a robot to: (i) obtain robot activity experiences from the robot’s performance in a dynamic environment; (ii) conceptualize each experience producing an activity schema; and (iii) exploit the learned activity schemata to make plans in similar situations. Experiences are episodic descriptions of plan-based robot activities including environment perception, sequences of applied actions and achieved tasks. The conceptualization approach integrates different techniques including deductive generalization, abstraction, goal inference and feature extraction. A high-level task planner was developed to find a solution for a task by following an activity schema. The proposed approach is illustrated and evaluated in a restaurant environment where a service robot learns how to carry out complex tasks. |
| Starting Page | 463 |
| Ending Page | 483 |
| Page Count | 21 |
| File Format | |
| ISSN | 09210296 |
| Journal | Journal of Intelligent & Robotic Systems |
| Volume Number | 83 |
| Issue Number | 3-4 |
| e-ISSN | 15730409 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2016-04-26 |
| Publisher Place | Dordrecht |
| Access Restriction | Subscribed |
| Subject Keyword | Robot task learning Task planning Experience-based planning domains Conceptualization Learning from human instructions Control, Robotics, Mechatronics Electrical Engineering Artificial Intelligence (incl. Robotics) Mechanical Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software |
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