A dual-layer multi-objective optimization method for structural and legged mechanism integrated design of heavy-duty hexapod robots

Existing design approaches for heavy-duty hexapod robots often treat the body layout and leg mechanism independently, which limits their ability to balance structural compactness, workspace coverage, and motion performance. To address this limitation, this study introduces a dual-layer multi-objective optimization framework that systematically integrates terrain constraints, geometric parameters, and dynamic feasibility to define a comprehensive feasible design domain. The first layer derives body layout parameters from analytical constraints associated with representative terrains, including slopes, lateral slopes, ravines, and obstacles. The second layer refines the leg link dimensions and scaling ratio to reduce joint forces and power consumption while satisfying the physically feasible constraints. The effectiveness is validated through simulation and hardware experiments. Results show that the optimized robot performs better than the baseline in joint force and power metrics and demonstrates strong terrain traversal capability across typical field scenarios. The framework provides a generalizable design methodology that can be extended to other legged robots with different body geometries or actuation schemes.