Petersen, Karen ; Kleiner, A. ; Stryk, Oskar von (2013)
Fast task-sequence allocation for heterogeneous robot teams with a human in the Loop.
doi: 10.1109/IROS.2013.6696570
Conference or Workshop Item, Bibliographie
Abstract
Efficient task allocation with timing constraints to a team of possibly heterogeneous robots is a challenging problem with application, e. g., in search and rescue. In this paper a mixed-integer linear programming (MILP) approach is proposed for assigning heterogeneous robot teams to the simultaneous completion of sequences of tasks with specific requirements such as completion deadlines. For this purpose our approach efficiently combines the strength of state of the art mixed-integer linear programming (MILP) solvers with human expertise in mission scheduling. We experimentally show that simple and intuitive inputs by a human user have substantial impact on both computation time and quality of the solution. The presented approach can in principle be applied to quite general missions for robot teams with human supervision.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2013 |
| Creators: | Petersen, Karen ; Kleiner, A. ; Stryk, Oskar von |
| Type of entry: | Bibliographie |
| Title: | Fast task-sequence allocation for heterogeneous robot teams with a human in the Loop |
| Language: | English |
| Date: | 2013 |
| Book Title: | Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) |
| DOI: | 10.1109/IROS.2013.6696570 |
| Abstract: | Efficient task allocation with timing constraints to a team of possibly heterogeneous robots is a challenging problem with application, e. g., in search and rescue. In this paper a mixed-integer linear programming (MILP) approach is proposed for assigning heterogeneous robot teams to the simultaneous completion of sequences of tasks with specific requirements such as completion deadlines. For this purpose our approach efficiently combines the strength of state of the art mixed-integer linear programming (MILP) solvers with human expertise in mission scheduling. We experimentally show that simple and intuitive inputs by a human user have substantial impact on both computation time and quality of the solution. The presented approach can in principle be applied to quite general missions for robot teams with human supervision. |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group |
| Date Deposited: | 20 Jun 2016 23:26 |
| Last Modified: | 08 May 2019 10:12 |
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