arXiv:2504.08615cs.RO2025-04中稿 · RSS 2025被引 5

用触觉天线让多足长身机器人能攀爬五倍身高的障碍物。

Tactile sensing enables vertical obstacle negotiation for elongate many-legged robots

  • 设计触觉天线探测障碍物结构,结合足部传感器反馈控制身体起伏。
  • 在实验室和户外测试中成功攀爬最高达身高的五倍的障碍物。
  • 适合需要低轮廓、高稳定性攀爬能力的复杂地形机器人研究者。

多足长身机器人在崎岖地形上展现出可靠的移动潜力。然而,现有研究大多聚焦于平面运动规划,未解决快速垂直运动问题。尽管在轻微崎岖地形表现良好,近期实地测试揭示了对三维行为(如攀爬或跨越高障碍)的迫切需求。三维运动规划的挑战部分源于为高自由度系统(通常超过25个自由度)设计感知与控制。为应对感知难题,我们提出一种触觉天线系统,使机器人能探测障碍物以获取其结构信息。基于此传感输入,我们构建了一套控制框架,整合天线与足部接触传感器数据,动态调整机器人的垂直体波运动以实现有效攀爬。仅通过添加简单、低带宽的触觉传感器,具有高静态稳定性和冗余性的机器人,在复杂环境中使用简单反馈控制器即可实现可预测的攀爬性能。实验表明,该机器人可在实验室及户外环境下攀爬高达其身高的五倍的障碍物。此外,其在覆盖移动随机物体或曲率快速变化的障碍物上也表现出稳健的攀爬能力。这些发现为腿部机器人提供了新的环境感知与响应策略,推动未来高适应性、低轮廓多足机器人的发展。

原文摘要 · Abstract (English)

Many-legged elongated robots show promise for reliable mobility on rugged landscapes. However, most studies on these systems focus on planar motion planning without addressing rapid vertical motion. Despite their success on mild rugged terrains, recent field tests reveal a critical need for 3D behaviors (e.g., climbing or traversing tall obstacles). The challenges of 3D motion planning partially lie in designing sensing and control for a complex high-degree-of-freedom system, typically with over 25 degrees of freedom. To address the first challenge regarding sensing, we propose a tactile antenna system that enables the robot to probe obstacles to gather information about their structure. Building on this sensory input, we develop a control framework that integrates data from the antenna and foot contact sensors to dynamically adjust the robot's vertical body undulation for effective climbing. With the addition of simple, low-bandwidth tactile sensors, a robot with high static stability and redundancy exhibits predictable climbing performance in complex environments using a simple feedback controller. Laboratory and outdoor experiments demonstrate the robot's ability to climb obstacles up to five times its height. Moreover, the robot exhibits robust climbing capabilities on obstacles covered with shifting, robot-sized random items and those characterized by rapidly changing curvatures. These findings demonstrate an alternative solution to perceive the environment and facilitate effective response for legged robots, paving ways towards future highly capable, low-profile many-legged robots.

多足机器人触觉感知攀爬控制3D运动

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