Streamlining Object Pushing: Behavior Tree-Based Coordination of Control and Planning

Efficiently navigating and manipulating objects in complex environments is a fundamental challenge in robotics. This paper presents a novel approach to streamline object-pushing tasks by integrating Behavior Trees (BT) to coordinate a control and planning framework. The proposed system optimizes the execution of tasks involving the pushing of objects while ensuring adaptability to varying scenarios.Our approach employs BTs to encapsulate high-level task specifications and decision-making processes, facilitating a flexible and intuitive representation of robot behavior. By seamlessly integrating BT technology with a coordinated control and planning system, we enable the robot to make real-time decisions and adapt to dynamic environments.We present experimental results demonstrating the effectiveness of our approach, highlighting its ability to improve task execution efficiency and adaptability.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802817
Primary Topic
Multi-Agent Systems and Negotiation
Type
article
Field-Weighted Citation Impact
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article

Streamlining Object Pushing: Behavior Tree-Based Coordination of Control and Planning

Filippo Bertoncelli, Lorenzo Sabattini
Multi-Agent Systems and Negotiation
article

Streamlining Object Pushing: Behavior Tree-Based Coordination of Control and Planning

Filippo Bertoncelli, Lorenzo Sabattini
article en

Abstract

Efficiently navigating and manipulating objects in complex environments is a fundamental challenge in robotics. This paper presents a novel approach to streamline object-pushing tasks by integrating Behavior Trees (BT) to coordinate a control and planning framework. The proposed system optimizes the execution of tasks involving the pushing of objects while ensuring adaptability to varying scenarios.Our approach employs BTs to encapsulate high-level task specifications and decision-making processes, facilitating a flexible and intuitive representation of robot behavior. By seamlessly integrating BT technology with a coordinated control and planning system, we enable the robot to make real-time decisions and adapt to dynamic environments.We present experimental results demonstrating the effectiveness of our approach, highlighting its ability to improve task execution efficiency and adaptability.

University of Modena and Reggio Emilia (IT), Technology Innovation Institute (AE)
Openalex Percentile: Top 78%
Multi-Agent Systems and Negotiation
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