Immersive Robot Programming Interface for Human-Guided Automation and Randomized Path Planning
Kaveh Malek, Claus Danielson, Fernando Moreu · ASME Letters in Translational Robotics · 2025
Abstract Researchers are exploring augmented reality (AR) interfaces for online robot programming to streamline automation and user interaction in various environments. This study designs, implements, and experimentally validates an AR interface for online programming and data visualization. This new interface integrates human manipulation in the randomized robot path planning, reducing the inherent randomness of the methods with human intervention. The interface uses holographic items that correspond to physical elements to interact with redundant robot manipulators. Utilizing rapidly random tree star (RRT*) and spherical linear interpolation (SLERP) algorithms, the interface achieves end-effector's progression through the collision-free path with smooth rotation. Next, sequential quadratic programming (SQP) achieve robot's configurations for this progression. The platform executes the RRT* algorithm in a loop, with each iteration independently exploring the shortest path through random sampling, leading to variations in the optimized paths produced. These paths are then demonstrated to AR users, who select the most appropriate path based on the environmental context and their intuition. The accuracy and effectiveness of the interface are validated through its implementation and testing with a 7-degrees-of-freedom (DOFs) manipulator, indicating its potential to optimize path planning and to advance current practices in robot programming.