Optimal Cost-Preference Trade-off Planning with Multiple Temporal Tasks

• URL: http://arxiv.org/abs/2306.13222v1
• Date: Thu, 22 Jun 2023 21:56:49 GMT
• Title: Optimal Cost-Preference Trade-off Planning with Multiple Temporal Tasks
• Authors: Peter Amorese and Morteza Lahijanian
• Abstract summary: We introduce a novel notion of preference that provides a generalized framework to express preferences over individual tasks as well as their relations. We perform an optimal trade-off (Pareto) analysis between behaviors that adhere to the user's preference and the ones that are resource optimal.
• Score: 3.655021726150368
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Autonomous robots are increasingly utilized in realistic scenarios with multiple complex tasks. In these scenarios, there may be a preferred way of completing all of the given tasks, but it is often in conflict with optimal execution. Recent work studies preference-based planning, however, they have yet to extend the notion of preference to the behavior of the robot with respect to each task. In this work, we introduce a novel notion of preference that provides a generalized framework to express preferences over individual tasks as well as their relations. Then, we perform an optimal trade-off (Pareto) analysis between behaviors that adhere to the user's preference and the ones that are resource optimal. We introduce an efficient planning framework that generates Pareto-optimal plans given user's preference by extending A* search. Further, we show a method of computing the entire Pareto front (the set of all optimal trade-offs) via an adaptation of a multi-objective A* algorithm. We also present a problem-agnostic search heuristic to enable scalability. We illustrate the power of the framework on both mobile robots and manipulators. Our benchmarks show the effectiveness of the heuristic with up to 2-orders of magnitude speedup.

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