To enhance the intelligence level of recreational robots assisting the elderly and disabled and address the intricate path planning challenge, this study investigates an optimized path planning method for such robots utilizing an improved ant colony algorithm. First, the robot’s working environment is modeled to precisely describe its motion state during path planning. Second, an initial path is generated based on the robot’s dynamic constraints and physical characteristics. Subsequently, the improved ant colony algorithm is applied, where the pheromone released by ants during the search process guides the search direction, continually optimizing the motion paths. Through redundancy processing of the optimized paths, optimal motion paths are generated. Test results demonstrate that, after applying the proposed method, the robot can promptly respond to task demands, commence execution, and reach the target position more swiftly, thereby improving overall motion efficiency.