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

Yuyang Chen, Dingkang Wang, Lenworth Thomas, Karthik Dantu, Sanjeev J. Koppal

TL;DR

A novel microelectromechanical mirror light detection and ranging (LiDAR) system to change the field of view of the LiDAR independent of the robot motion to simplify robot 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.

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

TL;DR

A novel microelectromechanical mirror light detection and ranging (LiDAR) system to change the field of view of the LiDAR independent of the robot motion to simplify robot 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.
Paper Structure (50 sections, 21 equations, 19 figures, 1 table)

This paper contains 50 sections, 21 equations, 19 figures, 1 table.

Figures (19)

  • Figure 1: Our design is given above with the prototype motion-compensated LiDAR (up), and we also prepared a design for future work to integrate this onto smaller platforms.
  • Figure 2: Biological motion compensation. The position and the angle of the head of the hawk remain stable despite body motion to provide the hawk an stabilized vision. https://www.youtube.com/watch?v=aqgewVCC0k0
  • Figure 3: (a) Representative simulation scenario - Blocks scene (b) Mapping the Blocks scene with compensation at 55Hz and no delay (c) Mapping the Blocks scene without compensation (d) Mapping the Blocks scene with compensation at 55Hz and delay of 150ms. (e) Mountains scene (f) mountains scene simulation with 55Hz compensation and 0ms delay (g) mountains scene simulation without compensation. (h) mountains scene simulation with 5Hz compensation and 0ms delay.
  • Figure 4: UAV odometry error while varying compensation rate and compensation delay in two scenes
  • Figure 5:
  • ...and 14 more figures