Multiresolution Motion Planning for Autonomous Agents via Wavelet-Based Cell Decompositions
Multiresolution Motion Planning for Autonomous Agents via Wavelet-Based Cell Decompositions
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DOI：
10.1109/tsmcb.2012.2192268
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发表时间：
2012-10-01
影响因子：
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通讯作者：
Tsiotras, Panagiotis
中科院分区：
文献类型：
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作者：
Cowlagi, Raghvendra V.;Tsiotras, Panagiotis
我们提出了一种“多分辨率”的路径和运动规划方案，既可以在局部以高精度表示环境，也可以在局部处理车辆的运动学和动力学约束。该方案采用矩形多分辨率单元分解，利用小波变换高效生成图像。小波变换在信号和图像处理中得到了广泛的应用，在自主传感和感知系统中得到了应用。所提出的运动规划器能够同时在车辆自主的感知和运动规划层中使用小波变换，从而潜在地减少在线计算。我们严格证明了所提出的路径规划方案的完备性，并给出了数值仿真结果来说明其有效性。
We present a path-and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.