OOPS for Motion Planning: An Online, Open-source, Programming System

The success of sampling-based motion planners has resulted in a plethora of methods for improving planning components, such as sampling and connection strategies, local planners and collision checking primitives. Although this rapid progress indicates the importance of the motion planning problem and the maturity of the field, it also makes the evaluation of new methods time consuming. We propose that a systems approach is needed for the development and the experimental validation of new motion planners and/or components in existing motion planners. In this paper, we present the online, open-source, programming system for motion planning (OOPS MP ), a programming infrastructure that provides implementations of various existing algorithms in a modular, object-oriented fashion that is easily extendible. The system is open-source, since a community-based effort better facilitates the development of a common infrastructure and is less prone to errors. We hope that researchers will contribute their optimized implementations of their methods and thus improve the quality of the code available for use. A dynamic Web interface and a dynamic linking architecture at the programming level allows users to easily add new planning components, algorithms, benchmarks, and experiment with different parameters. The system allows the direct comparison of new contributions with existing approaches on the same hardware and programming infrastructure

Authors

• Erion Plaku
• Kostas E. Bekris
• Lydia E. Kavraki

Keywords

• Open source software
• Dynamic programming
• Motion planning
• Strategic planning
• Sampling methods
• Object oriented programming
• Robotics and automation
• Automatic programming
• Robot programming
• Optimization methods
• Path Planning
• Benchmark
• Experimental Validation
• Urban Planning
• Planning System
• Collision Detection
• Planning Algorithm
• Infrastructure Programs
• Component Of Planning
• Valid Components
• Community-based Efforts
• Data Structure
• Hierarchical Structure
• Source Code
• State Space
• Algebra
• Projection Matrix
• Single Tree
• Submodule
• Core Module
• Rapidly-exploring Random Tree
• Multiple Queries
• Tree-based Algorithms