Towards a MEMS-based Adaptive LIDAR
This addresses the need for more flexible and efficient depth sensing in dynamic environments, though it appears incremental as a proof-of-concept.
The paper tackled the problem of enabling adaptive real-time depth measurements in LIDAR systems by developing a proof-of-concept design using a scanning MEMS mirror, and validated it on over 75 static and dynamic scenes with CNN-based depth-map completion experiments.
We present a proof-of-concept LIDAR design that allows adaptive real-time measurements according to dynamically specified measurement patterns. We describe our optical setup and calibration, which enables fast sparse depth measurements using a scanning MEMS (micro-electro-mechanical) mirror. We validate the efficacy of our prototype LIDAR design by testing on over 75 static and dynamic scenes spanning a range of environments. We show CNN-based depth-map completion experiments which demonstrate that our sensor can realize adaptive depth sensing for dynamic scenes.