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

TL;DR

This paper introduces a novel MEMS mirror LiDAR system that decouples sensor orientation from robot motion, enabling improved perception for small, low-power robots like UAVs by reducing jitter effects and simplifying perception tasks.

Contribution

The paper presents a new MEMS mirror LiDAR design that allows independent control of the sensor's field of view, suitable for small robots with limited computational resources.

Findings

Successful simulation validation of the system

Prototype hardware mounted on UAV demonstrates motion compensation

Decouples robot and sensor geometry for simplified perception

Abstract

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.