Search papers, labs, and topics across Lattice.
This paper introduces a Digital Twin-based Robotic Framework for Human-Robot Interaction (DTbRF-HRI) to enhance productivity, automation, and safety in smart manufacturing. The framework incorporates real-time data communication, a common digital model, and a simulation environment for obstacle avoidance and autonomous manipulation. The authors validate the framework's effectiveness through numerical simulation and physical experiments in an electronic consumer manufacturing scenario, demonstrating its robustness and practicability in improving intelligent robotic processes.
A digital twin framework slashes manufacturing errors by enabling real-time human-robot collaboration and predictive obstacle avoidance.
In the cyber-physical world, human-robot interaction (HRI) plays an increasingly important role in digital twin (DT)-enabled development, particularly in smart manufacturing. This investigation introduces a novel DT-based robotic framework for HRI (DTbRF-HRI), aiming to further productivity, automation, and safety. Our framework includes major elements such as real-time data communication, a common digital model, and a simulation environment for obstacle avoidance and autonomous manipulation. One contribution of our works is the application of an enhanced A-star algorithm for motion planning to support fast generation of paths and avoiding collisions. The data exchange between the physical and virtual agent is supported through system architecture and communication protocols, which meet with being very fast. The resulting framework is validated using numerical simulation and physical experiments in a common electronic consumer manufacturing scenario. Findings demonstrate the effectiveness, robustness, and practicability of DTbRF-HRI in improving intelligent robotic process in a cyber-physical system.
