In the International Journal of Computational Science and Engineering reports a new approach to autonomous robot navigation that could help prevent collisions and accidents in many future applications in a variety of environments such as industrial buildings and warehouses, farmlands and cities. the driverless car landscape, search and rescue locations, medical facilities, and even the home and garden.

Solving motion planning and control challenges, the key components that enable robots to move safely and efficiently, has been at the top of the research agenda for many years. Now, Jieyun Yu from Jinan University School of Mathematics in Guangzhou, China focused on two main aspects of overcoming problems: improving the performance of the control system and overcoming the limitations in path planning.

Yu was able to follow the correct trajectory using a new exponential feedback strategy based on iterative learning control (ILC) and model-independent adaptive control (MFAC). Its approach improves trajectory convergence, reduces errors, and provides precise and repeatable robot motion.

The path planning system also solves the collision avoidance problem by using an artificial potential field (APF) algorithm. In this case, obstacles in the robot’s path are considered driving forces in the virtual potential field, allowing the robot to bypass them without any obstacles. Yu ran simulations and tested the effectiveness of his approach, showing it to be more effective than traditional models.

Yu’s approach could enable a robot or autonomous vehicle to find a suitable and safe route much faster than other approaches, minimize avoidable errors, and enable robots to operate in complex and dynamic environments.

For example, this approach could be used to improve the behavior of autonomous vehicles by allowing autonomous vehicles to navigate a complex road network safely and accurately. In warehouse and industrial automation, the system can improve logistics, including the collection, sorting and transportation of goods and materials around the facility. The system also improves search and rescue robots, allowing them to work more effectively in disaster areas and navigate dangerous environments. In the fields, agricultural robotics will also benefit, thanks to more efficient plowing, planting, irrigation, monitoring and harvesting. Source