让蛇形机器人在无外部定位环境下自主导航
Enabling Autonomous Navigation in a Snake Robot through Visual-Inertial Odometry and Closed-Loop Trajectory Tracking Control
- 融合视觉惯性定位与闭环轨迹控制，实现自主导航
- 实测在动态移动中定位误差可控，支持多目标点追踪
- 适合行星探测、复杂地形探索等场景的自主机器人研发
蛇形机器人在极端地形中具有卓越移动能力，但其高度灵活的结构给无外部定位基础设施环境下的自主导航带来挑战。本论文为一款11自由度模块化蛇形机器人COBRA构建了完整的自主导航流程。尽管其仿生蛇形步态表现出色，此前研究完全依赖开环遥控操作。本文集成机载视觉惯性SLAM、降阶状态估计与闭环轨迹跟踪控制，实现基于航点的自主导航。配备深度相机与边缘计算单元，在动态运动中实时定位，并通过动作捕捉系统验证，量化了蛇形机器人特有的漂移行为与失效模式。采用降阶框架估计质心位姿，通过距离相关的偏航误差混合调节中央模式生成器（CPG）步态参数，驱动闭环控制器。物理实验验证了系统整体性能，实现了高精度多航点追踪，为蛇形机器人自主导航奠定基础。
原文摘要 · Abstract (English)
Snake robots offer exceptional mobility across extreme terrain inaccessible to conventional rovers, yet their highly articulated bodies present fundamental challenges for autonomous navigation in environments lacking external tracking infrastructure. This thesis develops a complete autonomy pipeline for COBRA, an 11 degree-of-freedom modular snake robot designed for planetary exploration. While the robot's biologically inspired serpentine gaits achieve impressive mobility, prior work has relied entirely on open-loop teleoperation. This approach integrates onboard visual-inertial SLAM, reduced-order state estimation, and closed-loop trajectory tracking to enable autonomous waypoint navigation. A depth camera paired with edge computing performs real-time localization during dynamic locomotion, validated against motion-capture ground truth to characterize drift behavior and failure modes unique to snake robot platforms. A reduced-order framework estimates Center-of-Mass pose, driving a closed-loop controller that modulates CPG gait parameters through distance-dependent yaw error blending. Physical experiments validate the complete system, demonstrating accurate multi-waypoint tracking and establishing foundations for autonomous snake robot navigation.
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