Three-dimensional Construction Path Planning Method for Lifting Robots Based on DME-DECSS algorithm

This paper proposes a novel three-dimensional construction path planning algorithm for lifting robots, termed DME-DECSS algorithm, which integrates the Dual-Modal Encoding mechanism with Dynamic Evolutionary Composite Sparrow Search. The proposed approach features two fundamental innovations: (1) The Dual-Modal Encoding mechanism that synergistically combines real-valued trajectory encoding with binary topological encoding for effective population initialization and evolutionary updating; (2)The Dynamic Evolutionary Composite Sparrow Search employs a multi-strategy composite framework, including dynamic subpopulation collaborative learning strategy, adaptive differential enhancement search strategy, exemplar-guided balanced learning strategy, and QIDG intelligent optimization strategy, to significantly improve solution quality and generate optimal paths for lifting robots. Experimental results demonstrate that this method can effectively plan collision-free and energy-optimal paths for lifting robots operating in complex construction environments with both static and dynamic obstacles.