Table 1 Summary of design frameworks targeted at diverse fields of robots.
Research | Research object | Research filed | Performance indices | Method |
|---|---|---|---|---|
Shi et al. (2024)45 | Climbing robot | Dimensional and structural design | Stability (hook attachment force), operation ability | Control variable method |
Gao et al. (2024)46 | Capsule robot | Driving system design | Power transfer efficiency (PTE), uniformity of alternating magnetic field | Variable impact analysis |
Sun et al. (2024)47 | Exoskeleton robot | Intelligent interactive control | Tracking accuracy, Convergence rate | Reinforcement learning neural network |
Zheng et al. (2022)48 | Welding robot | Offline programming (CAD and vision) | Welding time, welding task, welding efficiency ratio | Multi-objective optimization (genetic algorithm) |
Zhu (2023)49 | Mobile robot | Path planning and navigation | Navigation accuracy, obstacle avoidance, response time | Reinforcement learning and adaptive control |
Sun et al. (2024)50 | Quadruped Robot | Leg state estimation | Trajectory accuracy, time delay, computation cost | Probabilistic model with proprioceptive feedback |
Wang et al. (2024)51 | Machining serial robot | Equipment layout optimization | Kinematic performance (condition number), stiffness performance, machining accessibility | Single-objective optimization (sparrow search algorithm) |
Tian et al. (2024)52 | Collaborative robots | Trajectory tracking control | Tracking error | Single-objective optimization (Gradient-based optimization algorithm) |
Li et al. (2024)53 | Dual-robot collaborative system | Wire-arc additive manufacturing | Temperature gradient, residual stress, deformation | Finite element analysis |
Zheng et al. (2022)54 | Robotic manufacturing system | Manufacturing system architecture definition | Invest time and resources | Knowledge-based engineering |
