Quadrupedal robots are conquering various indoor and outdoor applications due to their ability to navigate challenging uneven terrains. Exteroceptive information greatly enhances this capability since perceiving their surroundings allows them to adapt their controller and thus achieve higher levels of robustness. However, sensors such as LiDARs and RGB cameras do not provide sufficient information to quickly and precisely react in a highly dynamic environment since they suffer from a bandwidth-latency tradeoff. They require significant bandwidth at high frame rates while featuring significant perceptual latency at lower frame rates, thereby limiting their versatility on resource-constrained platforms. In this work, we tackle this problem by equipping our quadruped with an event camera, which does not suffer from this tradeoff due to its asynchronous and sparse operation. In leveraging the low latency of the events, we push the limits of quadruped agility and demonstrate high-speed ball catching for the first time. We show that our quadruped equipped with an event camera can catch objects with speeds up to 15 m/s from 4 meters, with a success rate of 83%. Using a VGA event camera, our method runs at 100 Hz on an NVIDIA Jetson Orin.

翻译：四足机器人凭借其在复杂不平坦地形中的导航能力，正逐步征服各类室内外应用场景。外部感知信息极大增强了这一能力——通过感知周围环境，机器人可以调整控制器，从而实现更高等级的鲁棒性。然而，激光雷达（LiDAR）和RGB相机等传感器受限于带宽与延迟之间的权衡，无法在高度动态环境中快速精准地做出反应：高帧率运行时需要大量带宽，低帧率运行时则存在显著感知延迟，从而限制了其在资源受限平台上的通用性。本研究通过为四足机器人配备事件相机来攻克这一难题，事件相机凭借其异步稀疏的工作模式完全规避了上述权衡。通过利用事件流的低延迟特性，我们突破了四足机器人的敏捷性极限，首次实现了高速球体抓取。实验表明，配备事件相机的四足机器人能够在4米距离内以83%的成功率抓取速度高达15米/秒的物体。本研究采用VGA分辨率事件相机，在NVIDIA Jetson Orin平台上实现了100Hz的实时运行频率。