Robust Detection using sparse laser scanner with Autonomous Race Car

Pan Bo; Ni Jun; Hu Jibin

doi:10.1016/j.ifacol.2018.10.133

Robust Detection using sparse laser scanner with Autonomous Race Car

Pan Bo, Ni Jun, Hu Jibin

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

In this paper, a novel laser detection approach with lower objects is proposed. The detection method is based on RANSAC and another filter. For RANSAC, it detects ground surface and delete it in different driving condition. After that using Cluster, it can divide points into different groups which represents objects. Finally, there is a modified Formula SAE race car designed by author to finish experiment to test approach. We apply cones to combine track and do experiment in a random track to analysis the accuracy of detection.

Original language	English
Pages (from-to)	765-770
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	51
Issue number	31
DOIs	https://doi.org/10.1016/j.ifacol.2018.10.133
Publication status	Published - 2018
Event	5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2018 - Changchun, China Duration: 20 Sept 2018 → 22 Sept 2018

Keywords

RANSAC
autonomous race car
objects cluster
robust detection

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10.1016/j.ifacol.2018.10.133

Cite this

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title = "Robust Detection using sparse laser scanner with Autonomous Race Car",

abstract = "In this paper, a novel laser detection approach with lower objects is proposed. The detection method is based on RANSAC and another filter. For RANSAC, it detects ground surface and delete it in different driving condition. After that using Cluster, it can divide points into different groups which represents objects. Finally, there is a modified Formula SAE race car designed by author to finish experiment to test approach. We apply cones to combine track and do experiment in a random track to analysis the accuracy of detection.",

keywords = "RANSAC, autonomous race car, objects cluster, robust detection",

author = "Pan Bo and Ni Jun and Hu Jibin",

note = "Publisher Copyright: {\textcopyright} 2018; 5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2018 ; Conference date: 20-09-2018 Through 22-09-2018",

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AU - Jibin, Hu

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AB - In this paper, a novel laser detection approach with lower objects is proposed. The detection method is based on RANSAC and another filter. For RANSAC, it detects ground surface and delete it in different driving condition. After that using Cluster, it can divide points into different groups which represents objects. Finally, there is a modified Formula SAE race car designed by author to finish experiment to test approach. We apply cones to combine track and do experiment in a random track to analysis the accuracy of detection.

KW - RANSAC

KW - autonomous race car

KW - objects cluster

KW - robust detection

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U2 - 10.1016/j.ifacol.2018.10.133

DO - 10.1016/j.ifacol.2018.10.133

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VL - 51

SP - 765

EP - 770

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

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T2 - 5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2018

Y2 - 20 September 2018 through 22 September 2018

ER -

Robust Detection using sparse laser scanner with Autonomous Race Car

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Keywords

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