Autonomous navigation in unknown environments presents a critical challenge in the field of mobile robotics, with applications across industries such as logistics, defense, agriculture, and space exploration. The research group at the Department of Autonomous Systems focuses on the development of robust algorithms for real-time navigation, enabling robots to operate effectively in dynamic, unknown environments. This involves the integration of Simultaneous Localization and Mapping (SLAM) techniques, where robots concurrently create a map of their surroundings and track their position within that map, even in areas without GPS availability.

The group's research also explores bio-inspired robotic systems, drawing inspiration from natural organisms to enhance the adaptability and efficiency of robot movement in outdoor environments. These systems are designed to mimic biological motion and sensory processing, allowing robots to traverse complex terrains with the agility of animals. The development of artificial intelligence methods plays a significant role here, enabling robots to perceive their environment more accurately and make intelligent decisions in real time.

Cooperation with universities and research groups

• National Cheng-Kung University, Department of Mechanical Engineering, System Dynamics Lab. For Mechatronics and Microsystems, prof. Kuo-Shen Chen

• LUT University, Laboratory of Machine Design, Grzegorz Orzechowski

• National Taiwan University, Center for Artificial Intelligence and Advanced Robotics, prof. Pei-Chun Lin

Activities

• Best Paper Award – ICIAE Japan, A Framework on Analysis and Integration of Robot Manipulators for Smart Factory Applications

• European Commission member of Experts Round Table (ERT) for EU – Taiwan AI & Robotics panel

Contact person
Assoc. Prof. Stanislav Věchet