论文标题
生命：基于视觉的地形感知机器人
ViTAL: Vision-Based Terrain-Aware Locomotion for Legged Robots
论文作者
论文摘要
这项工作是针对腿部机器人的基于视觉的计划策略，这些机器人将运动计划分为立足点选择和姿势适应。当前的姿势适应策略优化了机器人的身体姿势相对于给定的立足。如果未达到这些立足点，机器人可能最终处于没有可伸到安全立足的状态。因此，我们提出了一种基于视觉的地形运动运动（重要）策略，该策略由新颖的姿势适应和立足点选择算法组成。 Vital引入了不同的姿势适应范式，该范式不会相对于给定的立足点优化身体的姿势，而是身体姿势可以最大程度地提高腿部在达到安全的立足点方面的机会。重要的计划立足和基于机器人能力及其地形意识的技能。 We use the 90 kg HyQ and 140 kg HyQReal quadruped robots to validate ViTAL, and show that they are able to climb various obstacles including stairs, gaps, and rough terrains at different speeds and gaits.我们将Cital与基线策略进行比较，该策略根据给定选定的立足点选择机器人姿势，并表明至关重要的表现优于基线。
This work is on vision-based planning strategies for legged robots that separate locomotion planning into foothold selection and pose adaptation. Current pose adaptation strategies optimize the robot's body pose relative to given footholds. If these footholds are not reached, the robot may end up in a state with no reachable safe footholds. Therefore, we present a Vision-Based Terrain-Aware Locomotion (ViTAL) strategy that consists of novel pose adaptation and foothold selection algorithms. ViTAL introduces a different paradigm in pose adaptation that does not optimize the body pose relative to given footholds, but the body pose that maximizes the chances of the legs in reaching safe footholds. ViTAL plans footholds and poses based on skills that characterize the robot's capabilities and its terrain-awareness. We use the 90 kg HyQ and 140 kg HyQReal quadruped robots to validate ViTAL, and show that they are able to climb various obstacles including stairs, gaps, and rough terrains at different speeds and gaits. We compare ViTAL with a baseline strategy that selects the robot pose based on given selected footholds, and show that ViTAL outperforms the baseline.
