  Perception in 3D has become standard practice for a large part of robotics
applications. High quality 3D perception is costly. Our previous work on a
nodding 2D Lidar provides high quality 3D depth information with low cost, but
the sparse data generated by this sensor poses challenges in understanding the
characteristics of moving objects within an uncertain environment. This paper
proposes a novel design of the nodding Lidar but provides dynamic
reconfigurability in terms of limiting the field of view of the sensor using a
set of optical mirrors. It not only provides denser scans, but it also achieves
a three times higher scan update rate. Additionally, we propose a novel
calibration mechanism for this sensor and prove its effectiveness for dynamic
object detection and tracking.

Computer Vision and Pattern Recognition;Robotics