Walking Principle of Four-legged Robot

Answer 1

The walking principle of the quadruped robot mainly involved the following aspects:
1. ** stability control **: This is the foundation of walking. The four-legged robot must maintain its balance and stability during walking. This required real-time monitoring of the robot's motion and posture, as well as coordinating the movements of its limbs. Common methods included zero-point stabilization, swing school control, and so on. The zero-point stabilization method achieved stability by controlling the acceleration of the center of gravity and its projection point to be zero, while the swing school control achieved stability by measuring and suppressing the angular velocity and angular acceleration of the robot body relative to gravity.
2. ** Gait Generation **: The gait of a quadruped robot refers to the relative motion of the limbs when walking. Continuous gait was generated according to the walking environment and speed requirements. For example, the gait of fast walking and slow walking was different. Gait generation required the movement trajectory, movement order, and relative movement relationship of the limbs to be clear.
3. ** Movement Control **: When walking, you need to control the angle and speed of each joint in real time to coordinate the limbs to achieve a complex movement trajectory. Commonly used methods included position control method, force control method, and hybrid control method. Position control was relatively simple but less robust; force control took into account the complexity of the mechanical model; hybrid control combined the advantages of both, using different methods at different stages.
4. ** Guidance and Obstacle Avoidance **: The four-legged robot had to plan its walking path based on environmental information, and it had to improve its adaptability through optimization of gait and control algorithms. It also had to sense the surrounding obstacles in real time to avoid obstacles. This required the robot to choose a path based on map and sensor information, detect and bypass obstacles in real-time, and usually use deep learning and operations research algorithms.
5. ** Learning and adaptation **: The four-legged robot needs to continuously accumulate walking experience with the help of learning algorithms to adapt to different ground environments and working conditions. For example, gait optimization based on reinforcement learning and visual navigation based on deep learning to improve the adaptability and intelligence of robots.