  Researchers are exploring Augmented Reality (AR) interfaces for online robot
programming to streamline automation and user interaction in variable
manufacturing environments. This study introduces an AR interface for online
programming and data visualization that integrates the human in the randomized
robot path planning, reducing the inherent randomness of the methods with human
intervention. The interface uses holographic items which correspond to physical
elements to interact with a redundant manipulator. Utilizing Rapidly Random
Tree Star (RRT*) and Spherical Linear Interpolation (SLERP) algorithms, the
interface achieves end-effector s progression through 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 seven Degree-OF-Freedom (DOF) manipulator, indicating its
potential to advance current practices in robot programming. The validation of
this paper include two implementations demonstrating the value of
human-in-the-loop and context awareness in robotics.
