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About this paper
Mian Guo, Kai Zhong, Xiaozhi Wang
An algorithm leveraging Frequency-Modulated Continuous-Wave (FMCW) LiDAR data enables real-time, single-scan detection and velocity estimation of moving objects for autonomous vehicles. The method achieves over 99% accuracy in motion classification and estimates velocities within 10 cm/s for objects with sufficient points, processing millions of points per second.
Key insights
- The inherent Doppler velocity information from FMCW LiDAR allows for single-scan motion state detection and velocity estimation, significantly reducing latency compared to multi-frame ToF LiDAR approaches.
- Points belonging to the same object exhibit continuous and similar Doppler velocities, enabling effective clustering and differentiation of moving objects from the static environment.
- A custom FMCW LiDAR model in CARLA provides a crucial, cost-effective platform for developing and validating advanced sensing algorithms without extensive real-world data collection.
Summary by alphaXiv.
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