Industrial Internet Robot Collaboration System and Edge Computing Optimization
Abstract
In industrial Internet environments, mobile robots must generate collision-free global routes under stochastic obstacle layouts and random perturbations in commanded linear and angular velocities. This paper models a differential-drive robot with nonholonomic constraints, then decomposes motion into obstacle avoidance, target turning, and target approaching behaviors to parameterize the control variables. Global path planning is formulated as a constrained optimization problem and converted into a weighted energy function that balances path length and collision penalties. A three-layer neural network represents the planning model, while simulated annealing searches for near-global minima and mitigates local traps. During execution, a fuzzy controller uses heading and lateral-offset errors to output wheel-speed differentials for rapid correction; edge-side computation is discussed to reduce robot-server traffic and latency. Matlab 2024 simulations report deviation within +-5 cm, convergence within 10 ms, and shorter paths than two baseline methods. The approach improves robustness of global navigation in practice.
Keywords
Cite
@article{arxiv.2504.02492,
title = {Industrial Internet Robot Collaboration System and Edge Computing Optimization},
author = {Haopeng Zhao and Dajun Tao and Tian Qi and Jingyuan Xu and Zijie Zhou and Lipeng Liu},
journal= {arXiv preprint arXiv:2504.02492},
year = {2026}
}