Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Kong, Christopher
Ferworn, Alex
Tran, Jimmy
Herman, Scott
Coleshill, Elliott
and
Derpanis, Konstantinos G.
2013.
Toward the automatic detection of access holes in disaster rubble.
p.
1.
Suger, Benjamin
Steder, Bastian
and
Burgard, Wolfram
2015.
Traversability analysis for mobile robots in outdoor environments: A semi-supervised learning approach based on 3D-lidar data.
p.
3941.
Kong, Christopher
Ferworn, Alex
Coleshill, Elliott
Tran, Jimmy
and
Derpanis, Konstantinos G.
2016.
What is a Hole? Discovering Access Holes in Disaster Rubble with Functional and Photometric Attributes.
Journal of Field Robotics,
Vol. 33,
Issue. 6,
p.
825.
Reddy, Satish Kumar
and
Pal, Prabir K.
2016.
Detection of traversable region around a mobile robot by computing terrain unevenness from the range data of a 3D laser scanner.
International Journal of Intelligent Unmanned Systems,
Vol. 4,
Issue. 2,
p.
107.
Shang, Erke
An, Xiangjing
Wu, Tao
Hu, Tingbo
Yuan, Qiping
and
He, Hangen
2016.
LiDAR Based Negative Obstacle Detection for Field Autonomous Land Vehicles.
Journal of Field Robotics,
Vol. 33,
Issue. 5,
p.
591.
Reddy, Satish Kumar
and
Pal, Prabir K.
2016.
Computing an unevenness field from 3D laser range data to obtain traversable region around a mobile robot.
Robotics and Autonomous Systems,
Vol. 84,
Issue. ,
p.
48.
Martínez, Jorge
Morán, Mariano
Morales, Jesús
Reina, Antonio
and
Zafra, Manuel
2018.
Field Navigation Using Fuzzy Elevation Maps Built with Local 3D Laser Scans.
Applied Sciences,
Vol. 8,
Issue. 3,
p.
397.
Lee, Hyunsuk
and
Chung, Woojin
2018.
Terrain Classification for Mobile Robots on the Basis of Support Vector Data Description.
International Journal of Precision Engineering and Manufacturing,
Vol. 19,
Issue. 9,
p.
1305.
KHAN, Muhammad Umer
2019.
Mobile Robot Navigation Using Reinforcement Learning in Unknown Environments.
Balkan Journal of Electrical and Computer Engineering,
Vol. 7,
Issue. 3,
p.
235.
Zhong, Zeyu
Wang, Zhiling
Lin, Linglong
Liang, Huawei
and
Xu, Fengyu
2020.
Robust Negative Obstacle Detection in Off-Road Environments Using Multiple LiDARs.
p.
700.
Matsubara, Kazuki
and
Nagatani, Keiji
2021.
Field and Service Robotics.
Vol. 16,
Issue. ,
p.
85.
Wu, Yutian
Wang, Yueyu
Zhang, Shuwei
and
Ogai, Harutoshi
2021.
Deep 3D Object Detection Networks Using LiDAR Data: A Review.
IEEE Sensors Journal,
Vol. 21,
Issue. 2,
p.
1152.
Sasaki, Taiga
and
Fujita, Toyomi
2021.
Gap Traversing Motion via a Hexapod Tracked Mobile Robot Based on Gap Width Detection.
Journal of Robotics and Mechatronics,
Vol. 33,
Issue. 3,
p.
665.
Hooper, Katrina
Ferworn, Alex
and
Hussain, Fatima
2021.
Advanced Information Networking and Applications.
Vol. 225,
Issue. ,
p.
220.
Hines, Thomas
Stepanas, Kazys
Talbot, Fletcher
Sa, Inkyu
Lewis, Jake
Hernandez, Emili
Kottege, Navinda
and
Hudson, Nicolas
2021.
Virtual Surfaces and Attitude Aware Planning and Behaviours for Negative Obstacle Navigation.
IEEE Robotics and Automation Letters,
Vol. 6,
Issue. 2,
p.
4048.
Malviya, Abhinav
and
Kala, Rahul
2022.
Learning-based simulation and modeling of unorganized chaining behavior using data generated from 3D human motion tracking.
Robotica,
Vol. 40,
Issue. 3,
p.
544.
César-Tondreau, Brian
Warnell, Garrett
Kochersberger, Kevin
and
Waytowich, Nicholas R.
2022.
Towards Fully Autonomous Negative Obstacle Traversal via Imitation Learning Based Control.
Robotics,
Vol. 11,
Issue. 4,
p.
67.
Islam, Fahmida
Nabi, M M
and
Ball, John E.
2022.
Off-Road Detection Analysis for Autonomous Ground Vehicles: A Review.
Sensors,
Vol. 22,
Issue. 21,
p.
8463.
Efondo, Arvin Bryan P.
Lagare, Jessa Mae S.
Canonigo, Paula Marie M.
and
Matillano-Perez, Engr. Elena
2023.
Development of LiDAR Navigation and BLE-RSSI Indoor Positioning for an Accident-Response Home-Bot.
p.
155.
Thakur, Abhishek
and
Mishra, Sudhansu Kumar
2024.
An in-depth evaluation of deep learning-enabled adaptive approaches for detecting obstacles using sensor-fused data in autonomous vehicles.
Engineering Applications of Artificial Intelligence,
Vol. 133,
Issue. ,
p.
108550.