Abstract
The specification of complex motion goals through temporal logics is increasingly favored in robotics to narrow the gap between task and motion planning. A major limiting factor of such logics, however, is their Boolean satisfaction condition. To relax this limitation, we introduce a method for quantifying the satisfaction of co-safe linear temporal logic specifications, and propose a planner that uses this method to synthesize robot trajectories with the optimal satisfaction value. The method assigns costs to violations of specifications from userdefined proposition costs. These violation costs define a distance to satisfaction and can be computed algorithmically using a weighted automaton. The planner utilizes this automaton and an abstraction of the robotic system to construct a product graph that captures all possible robot trajectories and their distances to satisfaction. Then, a plan with the minimum distance to satisfaction is generated by employing this graph as the high-level planner in a synergistic planning framework. The efficacy of the method is illustrated on a robot with unsatisfiable specifications in an office environment.
Original language | English |
---|---|
Title of host publication | Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 |
Publisher | AI Access Foundation |
Pages | 3664-3671 |
Number of pages | 8 |
ISBN (Electronic) | 9781577357032 |
State | Published - 1 Jun 2015 |
Externally published | Yes |
Event | 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 - Austin, United States Duration: 25 Jan 2015 → 30 Jan 2015 |
Publication series
Name | Proceedings of the National Conference on Artificial Intelligence |
---|---|
Volume | 5 |
Conference
Conference | 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 |
---|---|
Country/Territory | United States |
City | Austin |
Period | 25/01/15 → 30/01/15 |
Bibliographical note
Publisher Copyright:© Copyright 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.