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SkiROS2: A Skill-Based Robot Control Platform for ROS

Mayr, Matthias LU orcid ; Rovida, Francesco LU and Krueger, Volker LU orcid (2023) IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023 p.6273-6280
Abstract
The need for autonomous robot systems in both the service and the industrial domain is larger than ever. In the latter, the transition to small batches or even “batch size 1” in production created a need for robot control system architectures that can provide the required flexibility. Such architectures must not only have a sufficient knowledge integration framework. It must also support autonomous mission execution and allow for interchangeability and interoperability between different tasks and robot systems. We introduce SkiROS2, a skill-based robot control platform on top of ROS. SkiROS2 proposes a layered, hybrid control structure for automated task planning, and reactive execution, supported by a knowledge base for reasoning about... (More)
The need for autonomous robot systems in both the service and the industrial domain is larger than ever. In the latter, the transition to small batches or even “batch size 1” in production created a need for robot control system architectures that can provide the required flexibility. Such architectures must not only have a sufficient knowledge integration framework. It must also support autonomous mission execution and allow for interchangeability and interoperability between different tasks and robot systems. We introduce SkiROS2, a skill-based robot control platform on top of ROS. SkiROS2 proposes a layered, hybrid control structure for automated task planning, and reactive execution, supported by a knowledge base for reasoning about the world state and entities. The scheduling formulation builds on the extended behavior tree model that merges task-level planning and execution. This allows for a high degree of modularity and a fast reaction to changes in the environment. The skill formulation based on pre-, hold-and post-conditions allows to organize robot programs and to compose diverse skills reaching from perception to low-level control and the incorporation of external tools. We relate SkiROS2 to the field and outline three example use cases that cover task planning, reasoning, multisensory input, integration in a manufacturing execution system and reinforcement learning. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Robot Skills, Robots, Industrial Robots, Knowledge Representation, Reasoning, Planning
host publication
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
pages
8 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
conference location
Detroit, United States
conference dates
2023-10-01 - 2023-10-05
external identifiers
  • scopus:85174791043
ISBN
978-1-6654-9190-7
DOI
10.1109/IROS55552.2023.10342216
project
RobotLab LTH
Efficient Learning of Robot Skills
Robotics and Semantic Systems
SkiRoS: Skills for Robotic Systems for enabling agile production
Domain-Specific Robot Programming for Reliability, Safety, and Availability
SkiRoS: Skills for Robotic Systems for enabling agile production
Scalable automation for flexible production systems
WASP Professor Package: Cognitive Robots for Manufacturing
language
English
LU publication?
yes
id
6ccff6f8-1a55-4b8b-a7e5-bf32e6ec662f
alternative location
https://arxiv.org/abs/2306.17030
date added to LUP
2024-02-05 14:05:51
date last changed
2025-01-27 15:17:13
@inproceedings{6ccff6f8-1a55-4b8b-a7e5-bf32e6ec662f,
  abstract     = {{The need for autonomous robot systems in both the service and the industrial domain is larger than ever. In the latter, the transition to small batches or even “batch size 1” in production created a need for robot control system architectures that can provide the required flexibility. Such architectures must not only have a sufficient knowledge integration framework. It must also support autonomous mission execution and allow for interchangeability and interoperability between different tasks and robot systems. We introduce SkiROS2, a skill-based robot control platform on top of ROS. SkiROS2 proposes a layered, hybrid control structure for automated task planning, and reactive execution, supported by a knowledge base for reasoning about the world state and entities. The scheduling formulation builds on the extended behavior tree model that merges task-level planning and execution. This allows for a high degree of modularity and a fast reaction to changes in the environment. The skill formulation based on pre-, hold-and post-conditions allows to organize robot programs and to compose diverse skills reaching from perception to low-level control and the incorporation of external tools. We relate SkiROS2 to the field and outline three example use cases that cover task planning, reasoning, multisensory input, integration in a manufacturing execution system and reinforcement learning.}},
  author       = {{Mayr, Matthias and Rovida, Francesco and Krueger, Volker}},
  booktitle    = {{2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}},
  isbn         = {{978-1-6654-9190-7}},
  keywords     = {{Robot Skills; Robots; Industrial Robots; Knowledge Representation; Reasoning; Planning}},
  language     = {{eng}},
  month        = {{12}},
  pages        = {{6273--6280}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{SkiROS2: A Skill-Based Robot Control Platform for ROS}},
  url          = {{http://dx.doi.org/10.1109/IROS55552.2023.10342216}},
  doi          = {{10.1109/IROS55552.2023.10342216}},
  year         = {{2023}},
}