In response to the problem of prolonged operation time caused by inefficient and suboptimal trajectories of electric shovels during excavation, this paper proposes a robotic arm trajectory planning method based on an Improved Chicken Swarm Optimization (ICSO) algorithm. A trajectory planning experiment is conducted, where sequences of time and position in joint space are used to construct interpolation curves via quintic polynomial functions, with time as the optimization objective and joint angular velocity and acceleration of the robotic arm as constraints. The position update methods for the rooster, hen, and chick within the traditional Chicken Swarm Optimization (CSO) algorithm are refined, incorporating a series of new position update operations to form the ICSO algorithm. Comparative simulations between the ICSO and traditional CSO algorithms show that the improved algorithm significantly reduces the motion time of the robotic arm, effectively enhancing operational efficiency.