Name
Abstract | ||
|---|---|---|
This paper presents a framework developed for an industrial robotics system that utilises two different planning components. At a high level, a multi-robot mission planner interfaces with a fleet and environment manager and uses multi-agent planning techniques to build mission assignments to be distributed to a robot fleet. On each robot, a task planner automatically converts the robot's world model and skill definitions into a planning problem which is then solved to find a sequence of actions that the robot should perform to complete its mission. This framework is demonstrated on an industrial kitting task in a real-world factory environment. |
Year | Venue | Field |
|---|---|---|
2017 | Proceedings of the International Conference on Automated Planning and Scheduling | Geography of robotics,Software engineering,Computer science,Future of robotics,Knowledge management,Planner,Artificial intelligence,Factory environment,Robot,Machine learning,Industrial robotics |
DocType | ISSN | Citations |
Conference | 2334-0835 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matt Crosby | 1 | 12 | 1.45 |
| Ronald P. A. Petrick | 2 | 309 | 24.24 |
| francesco rovida | 3 | 12 | 2.80 |
| Volker Krüger | 4 | 1312 | 69.60 |