A real-time A algorithm for trajectories generation and collision avoidance in uncertain environments for assembly applications

• Published in: Computers & industrial engineering Vol. 202; p. 110959
• Main Authors: Nhouchi, Ahmed, Said, Salma Ben, Abdallah, Mohamed Amine Ben, Aifaoui, Nizar
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2025
• Subjects: A optimization algorithm; Artificial Intelligence; CAD model; Collision Avoidance; Robotic arm; Uncertain environment; Robotic arm; CAD model; Collision Avoidance; Uncertain environment; A optimization algorithm; Artificial Intelligence
• ISSN: 0360-8352
• DOI: 10.1016/j.cie.2025.110959

•Integration of a real-time A* algorithm with FreeCAD for improved trajectory generation and collision avoidance.•A comprehensive analysis of the impact of dynamic parameters on the pathfinding algorithm.•Incorporation of intelligent maneuvers (reversing, accelerating, decelerating) for adaptive and safe navigation in changing environments.•Optimize the production workflow for assembly-disassembly processes through collision reduction and improved efficiency.•Enhances CAD capabilities for diverse applications, leveraging Artificial Intelligence for real-time optimization and safety improvements. In assembly processes, generating paths and avoiding collisions are crucial for efficiency and safety. This paper presents a novel approach that integrates the A* pathfinding (PF) algorithm into FreeCAD, an open-source Computer-Aided Design (CAD) platform. The main contribution of this work is enabling PF and collision detection directly within the CAD environment during the design phase, helping detect potential collisions early and improving the design process. The A* algorithm has been adapted to handle both static and dynamic obstacles inside FreeCAD. This integration allows for better planning of paths in complex assembly environments. The integration process, algorithm modifications and system functionality are described in detail. A case study simulating an assembly line demonstrates the algorithm’s effectiveness in generating collision-free trajectories while adapting to dynamic changes in the environment. This work paves the way for further advancements in AI-driven CAD systems for industrial applications, enabling more intelligent and adaptive assembly processes during the design phase.