Applicability Analysis for Optical Cooperative Localization

For optical cooperative localization, which employs optical beacons with prior features as cooperative targets, a fundamental prerequisite is to ensure that the beacons are always captured by the vision sensors during the entire localization process. In other words, there is an applicability issue of optical cooperative localization with respect to the relative range between beacons and vision sensors, whereas the corresponding analysis method has so far remained a gap. In this work, we propose a general applicability analysis method for optical cooperative localization to fill this gap. We translate this problem into constructing a multi-constraint model incorporating geometrics and radiometrics for describing the relationship between optical sensor parameters and relative range or depth. For parameterized beacons and vision sensors, the geometric constraint is related to the imaging quantities and the radiometric constraint is determined by the radiation properties. Numerical evaluations are performed based on the range of parameters in practice, and real-world experiments are conducted to validate the effectiveness of the proposed applicability analysis. The results demonstrate the effectiveness of the proposed applicability analysis method and are instructive for real-world deployment of optical cooperative localization.

Authors

• Yixian Li
• Qiang Wang
• Jiaxing Wu
• Wuhong Zhao
• Shengrong Hu
• Zhonghu Hao

Keywords

• Location awareness
• Computational modeling
• Vision sensors
• Optical imaging
• Geometrical optics
• Radiometry
• Hardware
• Numerical models
• Optical sensors
• Intelligent robots
• Cooperative Localization
• Local Method
• Real-world Experiments
• Geometric Constraints
• Optical Parameters
• Relative Depth
• Optical Range
• Visible Light
• Image Pixels
• Focal Length
• Unmanned Aerial Vehicles
• Real-world Scenarios
• Feature Points
• Practical Scenarios
• Attenuation Coefficient
• Depth Estimation
• Focal Length Of Lens
• Sensor Size
• Camera Resolution
• Autonomous Underwater Vehicles
• Unmanned Ground Vehicles
• Hardware Parameters
• Luminal Area
• Field Of View Size
• Minimal Radiation
• Condenser Lens
• Radiation Attenuation
• Solid Angle
• Small Field Of View