A Tree-Based World Model for Reducing System Complexity in Autonomous Mobile Manipulation

Mobile manipulation tasks in unstructured environments remain challenging for autonomous robots. The need to employ a diverse set of software and hardware components to solve the various subtasks inevitably increases system complexity. Knowledge exchange among such diverse components renders them hi...

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Published in:IEEE robotics and automation letters Vol. 9; no. 7; pp. 6680 - 6687
Main Authors: Sakagami, Ryo, Domel, Andreas, Lehner, Peter, Riedel, Sebastian, Brunner, Sebastian G., Albu-Schaffer, Alin, Stulp, Freek
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.07.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Collision avoidance
Complexity theory
Decision making
End effectors
Geometric trees
Mobile manipulation
Motion planning
Navigation
Robot sensing systems
Software architecture
software architecture for robotic and automation
Task complexity
ISSN:2377-3766, 2377-3766
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Abstract Mobile manipulation tasks in unstructured environments remain challenging for autonomous robots. The need to employ a diverse set of software and hardware components to solve the various subtasks inevitably increases system complexity. Knowledge exchange among such diverse components renders them highly coupled, reduces communication efficiency, and makes the knowledge less accessible. To overcome these challenges, we propose AIMM-WM, a central world model as a single source of truth having an abstracted geometric tree structure. Despite its concise, efficient state representation, AIMM-WM is able to provide a wide range of information from low-level geometries to highly abstracted symbols and is interfaced with diverse components for navigation, motion planning, perception, decision-making, and mission control. We evaluate the performance of AIMM-WM from the real use case of our Lightweight Rover Unit during the four-week Moon-analogue demo mission on Mt. Etna, Italy.
AbstractList Mobile manipulation tasks in unstructured environments remain challenging for autonomous robots. The need to employ a diverse set of software and hardware components to solve the various subtasks inevitably increases system complexity. Knowledge exchange among such diverse components renders them highly coupled, reduces communication efficiency, and makes the knowledge less accessible. To overcome these challenges, we propose AIMM-WM, a central world model as a single source of truth having an abstracted geometric tree structure. Despite its concise, efficient state representation, AIMM-WM is able to provide a wide range of information from low-level geometries to highly abstracted symbols and is interfaced with diverse components for navigation, motion planning, perception, decision-making, and mission control. We evaluate the performance of AIMM-WM from the real use case of our Lightweight Rover Unit during the four-week Moon-analogue demo mission on Mt. Etna, Italy.
Author Lehner, Peter
Domel, Andreas
Sakagami, Ryo
Brunner, Sebastian G.
Riedel, Sebastian
Albu-Schaffer, Alin
Stulp, Freek
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Snippet Mobile manipulation tasks in unstructured environments remain challenging for autonomous robots. The need to employ a diverse set of software and hardware...
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SubjectTerms Collision avoidance
Complexity theory
Decision making
End effectors
Geometric trees
Mobile manipulation
Motion planning
Navigation
Robot sensing systems
Software architecture
software architecture for robotic and automation
Task complexity
Title A Tree-Based World Model for Reducing System Complexity in Autonomous Mobile Manipulation
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