MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641075660 A) filed by Sr University on June 18, 2026, for An Adaptive Learning-Based Grid Optimization Method For Autonomous Robot Navigation.
Inventors include Yeshwanth Kumar Md; and Rajchandar K.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: AN ADAPTIVE LEARNING-BASED GRID OPTIMIZATION METHOD FOR AUTONOMOUS ROBOT NAVIGATION The invention relates to an adaptive learning-based grid optimization method for autonomous robot navigation in dynamic environments. The method integrates reinforcement learning, environment density estimation, grid transformation, and learning memory to dynamically adjust grid resolution, density, and structure in real time. A reinforcement learning agent analyzes trajectory safety and efficiency, while an environment density estimator refines grid resolution in obstacle-rich regions. A grid transformer module splits or merges cells to balance computational efficiency with obstacle avoidance, and a learning memory stores high-risk regions for improved future path planning. The system minimizes computational cost in sparse areas and maximizes safety in dense zones, operating seamlessly across static and dynamic environments without reprogramming. The invention enhances path planning efficiency, reduces collision risk, and ensures robust autonomous navigation in complex, dynamic scenarios.
Disclaimer: Curated by HT Syndication.
