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Fast task-sequence allocation for heterogeneous robot teams with a human in the Loop

Petersen, Karen and Kleiner, A. and Stryk, Oskar von (2013):
Fast task-sequence allocation for heterogeneous robot teams with a human in the Loop.
In: Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), DOI: 10.1109/IROS.2013.6696570,
[Conference or Workshop Item]

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 and Kleiner, A. and Stryk, Oskar von
Title: Fast task-sequence allocation for heterogeneous robot teams with a human in the Loop
Language: English
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.

Title of Book: Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS)
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Date Deposited: 20 Jun 2016 23:26
DOI: 10.1109/IROS.2013.6696570
Identification Number: 2013:IROS
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