سبحان قايدزاده

Quadruped robots, due to their unique abilities in interacting with complex environments, are recognized as outstanding options for advanced navigation systems. Their agile and dynamic design enables movement along difficult paths, where wheeled robots face limitations. The ability of these robots to overcome large obstacles and move in various directions makes them an ideal choice for navigating rough terrains. On the other hand, a robust and efficient vision system can help robots accurately perceive their surroundings. Given these capabilities and the importance of navigation as a key indicators for autonomous robots, this research focuses on developing and implementing an advanced navigation system for the quadruped robot at the Iran University of Science and Technology. In this project, the main goal was to develop a navigation system for the quadruped robot that can autonomously move in complex environments. Inspired by well-known quadruped robots such as ANYmal and Mini-Cheetah, we aimed to follow similar navigation and path planning development processes of these robots. Considering the successful experiences of these robots in complex environments, we also implemented similar algorithms and drew inspiration from their agile and dynamic designs. To achieve this, vision and motion sensors, including the RealSense camera and IMU, were used to collect environmental data and construct elevation maps. Using the TEB and A* planning algorithms, the robot was able to identify and follow optimal paths in various environments. An important aspect was ensuring that the system operates in real-time, allowing the robot to continuously and pro‎mp‎tly make appropriate decisions when encountering obstacles and paths. The system was first implemented in a simulation, on a Core i7 processor and then on Jetson Nano. With proper system settings and optimization of system rates, the robot successfully moved in unknown environments and overcame obstacles. This project not only developed navigation algorithms but also examined the challenges of implementing them in real environments with limited hardware

Navigation, Path Planning, Elevation Mapping, Quadruped Robot, Robot Operating System