Where Should I Look? Optimised Gaze Control for Whole-Body Collision Avoidance in Dynamic Environments
Where Should I Look? Optimised Gaze Control for Whole-Body Collision Avoidance in Dynamic Environments
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DOI：
10.1109/lra.2021.3137545
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发表时间：
2022-04-01
影响因子：
5.2
通讯作者：
Havoutis, Ioannis
中科院分区：
文献类型：
--
作者：
Finean, Mark Nicholas;Merkt, Wolfgang;Havoutis, Ioannis
随着机器人在日益复杂和动态的环境中运行，快速运动重新规划已成为一个广泛探索的研究领域。在现实世界的部署中，我们通常缺乏随时全面观察环境的能力，这就带来了在不断更新的运动计划下确定如何最好地感知环境的挑战。我们提供了第一次调查到一个“智能”控制器的凝视控制，在动态和未知的环境中提供有效的感知环境的避障和运动规划的目标。我们详细介绍了新的问题，确定最佳的头部摄像头行为的移动的机器人时，受轨迹约束。此外，我们提出了一个贪婪的优化为基础的解决方案，使用体素化的奖励和运动原语的组合。我们证明，我们的方法优于基准方法在2D和3D环境中，在这两个方面的能力，探索当地的环境，以及在一个上级成功率找到无碰撞的轨迹-我们的方法被证明提供7.4倍更好的地图探索，同时始终实现更高的成功率生成无碰撞的轨迹。我们使用GPU加速感知框架验证了我们在物理丰田人类支持机器人（HSR）上的研究结果。
As robots operate in increasingly complex and dynamic environments, fast motion re-planning has become a widely explored area of research. In a real-world deployment, we often lack the ability to fully observe the environment at all times, giving rise to the challenge of determining how to best perceive the environment given a continuously updated motion plan. We provide the first investigation into a 'smart' controller for gaze control with the objective of providing effective perception of the environment for obstacle avoidance and motion planning in dynamic and unknown environments. We detail the novel problem of determining the best head camera behaviour for mobile robots when constrained by a trajectory. Furthermore, we propose a greedy optimization-based solution that uses a combination of voxelised rewards and motion primitives. We demonstrate that our method outperforms the benchmark methods in 2D and 3D environments, in respect of both the ability to explore the local surroundings, as well as in a superior success rate of finding collision-free trajectories - our method is shown to provide 7.4x better map exploration while consistently achieving a higher success rate for generating collision-free trajectories. We verify our findings on a physical Toyota Human Support Robot (HSR) using a GPU-accelerated perception framework.