OpenMORE: an open-source tool for sampling-based path replanning in ROS (2311.18406v1)

Abstract: With the spread of robots in unstructured, dynamic environments, the topic of path replanning has gained importance in the robotics community. Although the number of replanning strategies has significantly increased, there is a lack of agreed-upon libraries and tools, making the use, development, and benchmarking of new algorithms arduous. This paper introduces OpenMORE, a new open-source ROS-based C++ library for sampling-based path replanning algorithms. The library builds a framework that allows for continuous replanning and collision checking of the traversed path during the execution of the robot trajectory. Users can solve replanning tasks exploiting the already available algorithms and can easily integrate new ones, leveraging the library to manage the entire execution.

• The paper presents OpenMORE, a unified open-source framework for ROS that benchmarks sampling-based path replanning algorithms.
• It details a methodology that integrates continuous replanning with real-time collision detection and trajectory adjustments.
• The library’s modular design simplifies development and testing, promoting enhanced robot-human collaboration in dynamic environments.

Introduction

The robotic domain increasingly focuses on dynamic environments, where autonomous agents share spaces with humans or encounter unpredicted changes. Consequently, the ability to continuously and dynamically adapt planned paths—known as path replanning—has become critical. Among various methodologies, sampling-based path replanning techniques have emerged as a leading solution due to their efficiency in high-dimensional spaces. However, the robotics community has lacked a unified, open-source framework to benchmark and apply these algorithms effectively.

OpenMORE Library

To address this gap, OpenMORE, an open-source C++ library compatible with the Robot Operating System (ROS), has been developed to facilitate the creation, testing, and implementation of sampling-based path replanning algorithms. This library enables continuous replanning and concurrent management of execution, collision checking, and scene tracking. The user-friendly framework can seamlessly integrate existing algorithms and simplify the development of new ones, without requiring the construction of a complete architecture from scratch.

Core Concepts and Features

OpenMORE centers around two primary components: the replanner and replanner_manager. The former abstracts the replanning algorithm, while the latter orchestrates the overall replanning architecture. The library’s structure promotes the hassle-free extension of its functionalities, offering pre-designed tools for trajectory generation and collision detection adjustments that users may customize according to their algorithm's needs.

OpenMORE comes equipped with tools for data collection, real-time path visualization, and the simulation of unexpected obstacles. These features support debugging and performance benchmarking of replanning strategies. Also notable is the library's integration with ROS, which simplifies interaction with other software tools and complies with standard robotic frameworks and regulations in shared workspaces.

Conclusion and Future Directions

Overall, OpenMORE fosters an efficient and communal approach to studying and improving path replanning algorithms. Future iterations of the library will include even more detailed documentation and tutorials, generalize software dependencies, and potentially offer a ROS-free variant, expanding its applicability across different platforms. New users and experienced researchers alike could benefit from this dynamic, evolving tool, which has already proven successful in applications such as industrial robot-human collaborations and simulated dynamic environments.