This study aims to resolve the inherent conflict between obstacle-surmounting capability and payload platform stability in tracked robotic systems. A novel swing-arm tracked robot is proposed to enhance terrain adaptability while maintaining dynamic leveling and optimized center-of-gravity (CoG) distribution.
A parallel four-branch Chebyshev linkage mechanism is introduced to enable coupled payload pose regulation and CoG modulation. The workspace characteristics and feasible CoG distribution are quantitatively evaluated using a Monte Carlo-based stochastic sampling approach. Subsequently, integrated virtual simulations and prototype-level experimental validations are conducted to systematically assess slope-climbing capability and obstacle-surmounting performance under representative terrain conditions.
The robot successfully traverses a 300 mm trench, climbs a 30° soft slope and overcomes a 220 mm vertical obstacle. By CoG optimization analysis, obstacle height increases by 20 mm and climbing angle improves by 16°, demonstrating enhanced mobility and stability.
The proposed architecture integrates active leveling with CoG optimization through a novel linkage-based mechanism, offering a new technical pathway for designing high-mobility tracked robots in unstructured environments, particularly for reconnaissance and rescue applications.
