.png){kind=icon}
.png){kind=icon}
Return
Directional Sensor Planning for Occlusion Avoidance
.png){kind=icon}
PRE
AI
DOI：10.1109/TRO.2022.3180628.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Directional sensors, such as video cameras, have become ubiquitous to many autonomous robots applications, such as monitoring and surveillance. The performance of these sensors and processing algorithms, however, may be hindered by the presence of objects that block visibility. This article presents a novel approach for planning the path of a mobile directional sensor deployed to observe multiple targets distributed in an environment populated with multiple obstacles and occlusions. Unlike existing art gallery or watchman's route methods, the visibility theory and motion planners developed in this article account for both line-of-sight visibility and bounded field-of-view constraints, and can provide obstacle avoidance based on robot geometry and kinodynamic constraints. The computational complexity analysis and experiments on a camera-equipped drone demonstrate that, despite the challenging geometric characteristics of directional C-targets, the approach scales to real-world problems. Furthermore, when compared to algorithms inspired by traveling salesman and target coverage approaches, the directional visibility planners presented in this article are significantly more effective both at guaranteeing complete target visibility and at minimizing distance traveled.
Keywords:
Robot sensing systems
Robots
Cameras
Robot vision systems
Planning
Geometry
Aerospace electronics
Avoidance
camera
coverage
directional
line of sight (LOS)
obstacle
occlusion
path planning
sensor
visibility
target
Journal
IF:
10.5
Papers:
3.3K
Citations:
2.8W