Active Exploration and Mapping via Iterative Covariance Regulation over Continuous SE(3) Trajectories
Active Exploration and Mapping via Iterative Covariance Regulation over Continuous SE(3) Trajectories
复制标题
通过连续 SE(3) 轨迹的迭代协方差调节进行主动探索和映射
DOI：
10.1109/iros51168.2021.9636486
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Nikolay A. Atanasov
中科院分区：
文献类型：
--
作者：
Shumon Koga;Arash Asgharivaskasi;Nikolay A. Atanasov
本文提出了一种基于迭代协方差调节（iCR）的移动机器人主动探测与测绘新方法。该问题是对机器人的SE(3)位姿运动学进行最优控制，以最小化以潜在传感器观测为条件的地图的微分熵。引入可微视场公式，利用梯度下降法在连续空间中迭代更新开环控制序列，推导出iCR，使映射估计的协方差最小。我们在模拟占用网格环境中演示了自主探索和不确定性减少。
This paper develops iterative Covariance Regulation (iCR), a novel method for active exploration and mapping for a mobile robot equipped with on-board sensors. The problem is posed as optimal control over the SE(3) pose kinematics of the robot to minimize the differential entropy of the map conditioned the potential sensor observations. We introduce a differentiable field of view formulation, and derive iCR via the gradient descent method to iteratively update an open-loop control sequence in continuous space so that the covariance of the map estimate is minimized. We demonstrate autonomous exploration and uncertainty reduction in simulated occupancy grid environments.
影响因子：
3.5
作者：
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者：
Burgard, Wolfram
DOI：
10.1109/icra.2019.8793541
发表时间：
2019-05
期刊：
The International Journal of Robotics Research
影响因子：
--
作者：
Zhengdong Zhang;Theia Henderson;S. Karaman;V. Sze
通讯作者：
Zhengdong Zhang;Theia Henderson;S. Karaman;V. Sze