Estimating Visibility from Alternate Perspectives for Motion Planning with Occlusions
IEEE Robotics and Automation Letters(2024)
摘要
Visibility is a crucial aspect of planning and control of autonomous vehicles
(AV), particularly when navigating environments with occlusions. However, when
an AV follows a trajectory with multiple occlusions, existing methods evaluate
each occlusion individually, calculate a visibility cost for each, and rely on
the planner to minimize the overall cost. This can result in conflicting
priorities for the planner, as individual occlusion costs may appear to be in
opposition. We solve this problem by creating an alternate perspective cost map
that allows for an aggregate view of the occlusions in the environment. The
value of each cell on the cost map is a measure of the amount of visual
information that the vehicle can gain about the environment by visiting that
location. Our proposed method identifies observation locations and occlusion
targets drawn from both map data and sensor data. We show how to estimate an
alternate perspective for each observation location and then combine all
estimates into a single alternate perspective cost map for motion planning.
更多查看译文
关键词
Planning under Uncertainty,Motion and Path Planning,Integrated Planning and Control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要