Author:
Mansouri Masoumeh,Pecora Federico,Schüller Peter
Abstract
Combined Task and Motion Planning (TAMP) is an area where no one-fits-all solution can exist. Many aspects of the domain, as well as operational requirements, have an effect on how algorithms and representations are designed. Frequently, trade-offs have to be made to build a system that is effective. We propose five research questions that we believe need to be answered to solve real-world problems that involve combined TAMP. We show which decisions and trade-offs should be made with respect to these research questions, and illustrate these on examples of existing application domains. By doing so, this article aims to provide a guideline for designing combined TAMP solutions that are adequate and effective in the target scenario.
Subject
Artificial Intelligence,Computer Science Applications
Reference48 articles.
1. A Review of Learning Planning Action Models;Arora;Knowl. Eng. Rev.,2018
2. Learning Action Models for Navigation in Noisy Environments;Balac,2000
3. Integrated, Plan-Based Control of Autonomous Robot in Human Environments;Beetz;IEEE Intell. Syst.,2001
4. A Constraint Programming Approach to Simultaneous Task Allocation and Motion Scheduling for Industrial Dual-Arm Manipulation Tasks;Behrens
5. Specifying Dual-Arm Robot Planning Problems through Natural Language and Demonstration;Behrens;IEEE Robot. Autom. Lett.
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献