基于改进蚁群算法的四足机器人步态规划

四足机器人关节众多、运动方式复杂，步态规划是四足机器人运动控制的基础。传统的算法多基于仿生原理，缺乏广泛适应性。 在建立运动学方程的基础上，提出了一种基于改进蚁群算法的步态规划算法。该算法利用了四足机器人4条腿运动的线性无关性，将步态规划问题转换为在四维空间里求取最长路径问题。仿真结果表明，该算法得出了满足约束条件的所有步态，最后通过机器人样机检验，验证了该算法求取结果的有效性和合理性。

Gait planning of quadruped robots based on an improved ant colony algorithm

quadruped robots have many joints and complex motion modes. Gait planning is the basis of the motion control of the quadruped robot. Traditional algorithms are mostly based on the principle of bionics and lack wide adaptability. Based on the establishment of kinematics equations, this paper proposes a gait planning algorithm based on an improved ant colony algorithm. The algorithm takes advantage of the linear independence of four legs of the robots, and classifies the gait planning problem as a problem of how to plan the longest path in a four-dimension space. After simulation, the algorithm obtains all gaits meeting the constraints. Finally, the robot prototype was tested to verify the validity and rationality of the results obtained by the algorithm.