While the transport of matter by wheeled vehicles or legged robots can be guaranteed in engineered landscapes like roads or rails, locomotion prediction in complex environments like collapsed buildings or crop fields remains challenging. Inspired by principles of information transmission which allow signals to be reliably transmitted over noisy channels, we develop a ``matter transport" framework demonstrating that non-inertial locomotion can be provably generated over ``noisy" rugose landscapes (heterogeneities on the scale of locomotor dimensions). Experiments confirm that sufficient spatial redundancy in the form of serially-connected legged robots leads to reliable transport on such terrain without requiring sensing and control. Further analogies from communication theory coupled to advances in gaits (coding) and sensor-based feedback control (error detection/correction) can lead to agile locomotion in complex terradynamic regimes.

翻译：尽管轮式车辆或腿式机器人能够在诸如道路或轨道等工程化地形上保证物质传输，但在倒塌建筑或农田等复杂环境中的运动预测仍具挑战性。受信息传输原理的启发——该原理允许信号在噪声信道中可靠传递——我们发展了一个"物质传输"理论框架，证明非惯性运动可在"噪声"崎岖地形（异质性尺度与运动器尺寸相当）上被可靠生成。实验证实，以串联连接的腿式机器人形式存在的充分空间冗余，可在无需传感与控制的情况下实现此类地形的可靠传输。源自通信理论的进一步类比，结合步态（编码）与基于传感器的反馈控制（误差检测/校正）的进步，可引领复杂非惯性动力学场景中的敏捷运动。