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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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An Analytic Model for Negative Obstacle Detection with Lidar and Numerical Validation Using Physics-Based Simulation.

Christopher Goodin1, Justin Carrillo2, J Gabriel Monroe2

  • 1Center for Advanced Vehicular Systems, Mississippi State University, Mississippi State, MS 39762, USA.

Sensors (Basel, Switzerland)
|June 2, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an analytical model for lidar-based negative obstacle detection in autonomous navigation. UAV-mounted lidar significantly improves detection range (60-110m) compared to ground vehicle systems (<10m).

Keywords:
UAVautonomylidarnavigation

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Area of Science:

  • Robotics
  • Autonomous Systems
  • Sensor Technology

Background:

  • Autonomous navigation for ground vehicles faces challenges with negative obstacles.
  • Advancements in lighter, cost-effective terrestrial lidar sensors enable their use on unmanned aerial vehicles (UAVs).

Purpose of the Study:

  • To develop an analytical model for predicting negative obstacle detection capabilities of lidar sensors mounted on UAVs or ground vehicles (UGVs).
  • To analyze the influence of sensor rotation rate, vehicle speed, and view angles on detection range.
  • To determine limiting speeds for safe autonomous navigation based on stopping distance.

Main Methods:

  • Development of an analytical model incorporating sensor rotation rate and vehicle speed.
  • Validation of the model using a physics-based simulator in realistic terrain.
  • Comparison of detection ranges for UAV-mounted versus UGV-mounted lidar systems.

Main Results:

  • The analytical model is validated for altitudes above 10 meters.
  • UAV-mounted lidar demonstrates significantly improved negative obstacle detection ranges (60-110 meters) compared to UGV-mounted lidar (<10 meters).
  • Detection range is influenced by UAV speed and lidar type.

Conclusions:

  • The developed analytical model accurately predicts negative obstacle detection performance.
  • UAV-mounted lidar offers a substantial advantage for detecting negative obstacles in autonomous navigation.
  • The findings provide critical insights for optimizing autonomous vehicle navigation strategies.