MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641062244 A) filed by Srujana Inturi; Guda Vanitha; Dr. Nagini Yarramsetty; Ms. Varimadugu Sandhya; Ms. Jyothirmayi Narne; Dr. V Jaipal Reddy; Eliganti Ramalakshmi; and Dr. O. Hemalatha, Hyderabad, Telangana, on May 16, for 'terrain-adaptive mobility architecture for autonomous delivery platforms.'
Inventor(s) include Srujana Inturi; Guda Vanitha; Dr. Nagini Yarramsetty; Ms. Varimadugu Sandhya; Ms. Jyothirmayi Narne; Dr. V Jaipal Reddy; Eliganti Ramalakshmi; and Dr. O. Hemalatha.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a terrain-adaptive mobility architecture for autonomous delivery platforms configured to operate efficiently across diverse terrain and environmental conditions. The disclosed system integrates a terrain sensing module, adaptive mobility control unit, intelligent navigation subsystem, machine learning-based terrain classification engine, and real-time processing controller within a unified autonomous delivery framework. The terrain sensing module continuously acquires environmental and surface-related information using cameras, ultrasonic sensors, inertial measurement units, LiDAR sensors, and proximity detectors. The collected data is processed to identify terrain characteristics including surface roughness, inclination, friction conditions, and obstacle distribution. Based on the analysed terrain data, the adaptive mobility control unit dynamically modifies locomotion parameters including wheel torque, steering response, traction distribution, suspension behaviour, braking force, and chassis stability to improve maneuverability and operational safety. The intelligent navigation subsystem performs adaptive route planning and real-time path optimization according to terrain complexity, environmental constraints, and delivery requirements. The invention further incorporates predictive mobility analysis and machine learning-assisted terrain classification mechanisms for anticipating mobility risks and optimizing movement strategies before operational instability occurs. Additionally, the system includes an energy optimization module configured to regulate power consumption according to terrain resistance and movement requirements, thereby improving battery efficiency and operational endurance. The disclosed architecture enables seamless operation across structured, semi-structured, and unstructured environments while reducing wheel slippage, navigation failures, and mobility interruptions. Accordingly, the invention provides an intelligent, scalable, and terrain-responsive autonomous delivery framework suitable for smart logistics and last-mile delivery applications."
Disclaimer: Curated by HT Syndication.
