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Anticipate your surroundings: Predictive collision detection between dynamic obstacles and planned robot trajectories on the GPU

机译:预测周围环境:在GPU上动态障碍物和计划的机器人轨迹之间进行预测性碰撞检测

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Proactive collision detection enables robots to efficiently execute tasks in shared human-robot-workspaces by avoiding collision-prone situations. Our work connects motion prediction of RGB-D flow algorithms with motion primitive planning via an efficient voxel Swept-Volume-based collision detection. The approach can handle scenarios with varying contents as we use the same techniques to predict single moving objects but also articulated bodies. Our process chain consists of highly parallel GPU algorithms that allow a full 3D representation of planned trajectories and predictions from live pointclouds in high resolution, while still being online capable. We demonstrated our achievements in two scenarios with different motion granularity.
机译:主动碰撞检测使机器人能够避免容易发生碰撞的情况,从而有效地在共享的人类机器人工作空间中执行任务。我们的工作通过高效的基于体素扫掠体的碰撞检测将RGB-D流算法的运动预测与运动原始规划联系起来。由于我们使用相同的技术来预测单个移动的物体但也可以预测关节的物体,因此该方法可以处理具有不同内容的场景。我们的流程链由高度并行的GPU算法组成,该算法可在不中断在线的情况下,以高分辨率对实时点云中的计划轨迹和预测进行完整的3D表示。我们在两种具有不同运动粒度的场景中展示了我们的成就。

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