Core Viewpoint - The research focuses on developing an advanced Central Pattern Generator (CPG) for quadruped robots, enhancing their locomotion capabilities and enabling more complex and adaptive movements compared to existing models [3][21]. Group 1: CPG Development - The existing four-neuron CPG architectures are limited in functionality, typically generating no more than three types of gaits, while natural quadrupeds can exhibit over six [2][3]. - A new eight-neuron CPG network was developed based on symmetry principles, allowing for better coordination of multi-joint movements in quadruped robots [3][4]. Group 2: Gait Generation and Control - The research team demonstrated that a symmetric four-neuron network could theoretically produce five different gaits, including walking, trotting, and jumping [4][7]. - The eight-neuron CPG network was designed to independently control the hip and knee joints of each leg, significantly improving the robot's movement coordination [5][9]. Group 3: Gait Transition Strategies - The team identified four effective strategies for smooth gait transitions: Direct Switch, Power Pair, Wait & Switch, and Wait & Power Pair, ensuring high success rates during transitions [11][12]. - The new CPG network achieved nearly 100% success in transitioning between walking, trotting, and pacing, even outperforming existing solutions in more complex transitions [15][17]. Group 4: Sensor Integration and Adaptability - Two sensor integration frameworks were developed: one for visual path tracking and another for proprioceptive feedback, enhancing the robot's adaptability to different terrains [18][21]. - The integration of these sensors allows the robot to autonomously switch gaits based on environmental conditions, demonstrating a significant improvement in adaptability and stability [21].