Legged robots can outperform wheeled machines for most navigation tasks across unknown and rough terrains. For such tasks, visual feedback is a fundamental asset to provide robots with terrain-awareness. However, robust dynamic locomotion on difficult terrains with real-time performance guarantees remains a challenge. We present here a real-time, dynamic foothold adaptation strategy based on visual feedback. Our method adjusts the landing position of the feet in a fully reactive manner, using only on-board computers and sensors. The correction is computed and executed continuously along the swing phase trajectory of each leg. To efficiently adapt the landing position, we implement a self-supervised foothold classifier based on a Convolutional Neural Network (CNN). Our method results in an up to 200 times faster computation with respect to the full-blown heuristics. Our goal is to react to visual stimuli from the environment, bridging the gap between blind reactive locomotion and purely vision-based planning strategies. We assess the performance of our method on the dynamic quadruped robot HyQ, executing static and dynamic gaits (at speeds up to 0.5 m/s) in both simulated and real scenarios; the benefit of safe foothold adaptation is clearly demonstrated by the overall robot behavior.
Summary This paper introduces a robust observer‐based output feedback control strategy that enables the generation of complex three‐dimensional borehole trajectories created by directional drilling systems, while avoiding undesired transient behavior. The model‐based controller relies on a set of nonlinear delay differential equations describing the borehole evolution. Herein, only local orientation measurements of the bottom hole assembly of the drilling system are employed. Controller and observer gains are synthesized by optimizing the location of the rightmost pole of the closed‐loop dynamics, using a spectral approach for delay differential equations. Moreover, the strategy is extended to cope with the uncertainty of key system parameters in the directional drilling process. The effectiveness of the designed controller is tested in an illustrative benchmark study.
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