Design of an Adaptive Lightweight LiDAR to Decouple Robot-Camera Geometry

by   Yuyang Chen, et al.

A fundamental challenge in robot perception is the coupling of the sensor pose and robot pose. This has led to research in active vision where robot pose is changed to reorient the sensor to areas of interest for perception. Further, egomotion such as jitter, and external effects such as wind and others affect perception requiring additional effort in software such as image stabilization. This effect is particularly pronounced in micro-air vehicles and micro-robots who typically are lighter and subject to larger jitter but do not have the computational capability to perform stabilization in real-time. We present a novel microelectromechanical (MEMS) mirror LiDAR system to change the field of view of the LiDAR independent of the robot motion. Our design has the potential for use on small, low-power systems where the expensive components of the LiDAR can be placed external to the small robot. We show the utility of our approach in simulation and on prototype hardware mounted on a UAV. We believe that this LiDAR and its compact movable scanning design provide mechanisms to decouple robot and sensor geometry allowing us to simplify robot perception. We also demonstrate examples of motion compensation using IMU and external odometry feedback in hardware.


page 1

page 2

page 4

page 8

page 9

page 10

page 12

page 18


A Biologically Inspired Simultaneous Localization and Mapping System Based on LiDAR Sensor

Simultaneous localization and mapping (SLAM) is one of the essential tec...

Self-supervised Learning of LiDAR Odometry for Robotic Applications

Reliable robot pose estimation is a key building block of many robot aut...

M-LIO: Multi-lidar, multi-IMU odometry with sensor dropout tolerance

We present a robust system for state estimation that fuses measurements ...

A MEMS-based Foveating LIDAR to enable Real-time Adaptive Depth Sensing

Most active depth sensors sample their visual field using a fixed patter...

Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry

We present an efficient multi-sensor odometry system for mobile platform...

Low Frequency Spinning LiDAR De-Skewing

Most commercially available Light Detection and Ranging (LiDAR)s measure...

Follow Pedro! An Infrared-based Person-Follower using Nonlinear Optimization

We used ROS2 as a platform to conduct AI research for developing a Follo...

Please sign up or login with your details

Forgot password? Click here to reset