Experimental validation demonstrates enhanced slope-climbing and obstacle navigation in a swing-arm tracked robot, highlighting the value of linkage-based dynamic center-of-gravity modulation.
Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.
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Hao et al. (2026) studied this question.
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