{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:14:09Z","timestamp":1760238849125,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,5]],"date-time":"2020-09-05T00:00:00Z","timestamp":1599264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51575463","51905460"],"award-info":[{"award-number":["51575463","51905460"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Project in Science and Technology Plan of Xiamen","award":["3502Z20191019"],"award-info":[{"award-number":["3502Z20191019"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Obstacle detection is one of the essential capabilities for autonomous robots operated on unstructured terrain. In this paper, a novel laser-based approach is proposed for obstacle detection by autonomous robots, in which the Sobel operator is deployed in the edge-detection process of 3D laser point clouds. The point clouds of unstructured terrain are filtered by VoxelGrid, and then processed by the Gaussian kernel function to obtain the edge features of obstacles. The Euclidean clustering algorithm is optimized by super-voxel in order to cluster the point clouds of each obstacle. The characteristics of the obstacles are recognized by the Levenberg\u2013Marquardt back-propagation (LM-BP) neural network. The algorithm proposed in this paper is a post-processing algorithm based on the reconstructed point cloud. Experiments are conducted by using both the existing datasets and real unstructured terrain point cloud reconstructed by an all-terrain robot to demonstrate the feasibility and performance of the proposed approach.<\/jats:p>","DOI":"10.3390\/s20185048","type":"journal-article","created":{"date-parts":[[2020,9,6]],"date-time":"2020-09-06T23:12:49Z","timestamp":1599433969000},"page":"5048","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Novel Laser-Based Obstacle Detection for Autonomous Robots on Unstructured Terrain"],"prefix":"10.3390","volume":"20","author":[{"given":"Wei","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, China"}]},{"given":"Qianjie","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5797-1412","authenticated-orcid":false,"given":"Huosheng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science &amp; Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK"}]},{"given":"Jun","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, China"}]},{"given":"Shaojie","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5521-5023","authenticated-orcid":false,"given":"Qingyuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"914","DOI":"10.1002\/rob.20401","article-title":"Autonomous transportation and deployment with aerial robots for search and rescue missions","volume":"28","author":"Bernard","year":"2011","journal-title":"J. Field Robot."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dooraki, A.R., and Lee, D.J. (2018). An end-to-end deep reinforcement learning-based intelligent agent capable of autonomous exploration in unknown environments. Sensors, 18.","DOI":"10.3390\/s18103575"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0020-0255(02)00221-9","article-title":"Intelligent learning and control of autonomous robotic agents operating in unstructured environments","volume":"145","author":"Hagras","year":"2002","journal-title":"Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1002\/rob.21795","article-title":"Weaver: Hexapod robot for autonomous navigation on unstructured terrain","volume":"35","author":"Bjelonic","year":"2018","journal-title":"J. Field Robot."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Kolar, P., Benavidez, P., and Jamshidi, M. (2020). Survey of datafusion techniques for laser and vision based sensor integration for autonomous navigation. Sensors, 20.","DOI":"10.3390\/s20082180"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1002\/rob.21794","article-title":"High-precision control of tracked field robots in the presence of unknown traction coefficients","volume":"35","author":"Kayacan","year":"2018","journal-title":"J. Field Robot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.1109\/TASE.2019.2910508","article-title":"Unsupervised machine learning based scalable fusion for active perception","volume":"16","author":"Jayaratne","year":"2019","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2599","DOI":"10.1109\/TITS.2015.2413971","article-title":"Vision-based night-time vehicle detection using CenSurE and SVM","volume":"16","author":"Kosaka","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1109\/TITS.2012.2188630","article-title":"Vision-based vehicle detection system with consideration of the detecting location","volume":"13","author":"Cheon","year":"2012","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1469","DOI":"10.1002\/rob.21724","article-title":"Online covariance estimation for novelty-based visual obstacle detection","volume":"34","author":"Ross","year":"2017","journal-title":"J. Field Robot."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"10753","DOI":"10.3390\/s140610753","article-title":"Obstacle classification and 3D measurement in unstructured environments based on ToF cameras","volume":"14","author":"Yu","year":"2014","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1109\/TITS.2016.2565698","article-title":"Rapid localization and extraction of street light poles in mobile LiDAR point clouds: A Supervoxel-based approach","volume":"18","author":"Wu","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Pang, C., Zhong, X.Y., Hu, H.S., Tian, J., Peng, X.F., and Zeng, J.P. (2018). Adaptive obstacle detection for mobile robots in urban environments using downward-looking 2D LiDAR. Sensors, 18.","DOI":"10.3390\/s18061749"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4652","DOI":"10.3390\/rs5094652","article-title":"Synthesis of transportation applications of mobile LiDAR","volume":"5","author":"Williams","year":"2013","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compag.2016.03.017","article-title":"Evaluation of a LiDAR-based 3D-stereoscopic vision system for crop-monitoring applications","volume":"124","author":"Bietresato","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2167","DOI":"10.1109\/TITS.2015.2399492","article-title":"Automated extraction of urban road facilities using mobile laser scanning data","volume":"16","author":"Yu","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1824","DOI":"10.1109\/TITS.2016.2616718","article-title":"A combined voxel and particle filter-based approach for fast obstacle detection and tracking in automotive applications","volume":"18","author":"Morales","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Wang, Z., Liu, H., Qian, Y.L., and Xu, T. (2012, January 7\u201313). Real-Time Plane Segmentation and Obstacle Detection of 3D Point Clouds for Indoor Scenes. Proceedings of the 12th European Conference on Computer Vision (ECCV), Florence, Italy.","DOI":"10.1007\/978-3-642-33868-7_3"},{"key":"ref_19","first-page":"275","article-title":"Indoor navigation from point clouds: 3D modelling and obstacle detection","volume":"41","author":"Boguslawski","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Fountas, S., Mylonas, N., Malounas, I., Rodias, E., Santos, C.H., and Pekkeriet, E. (2020). Agricultural Robotics for Field Operations. Sensors, 20.","DOI":"10.3390\/s20092672"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Bazazian, D., Casas, J.R., and Ruiz-Hidalgo, J. (2015, January 23\u201325). Fast and Robust Edge Extraction in Unorganized Point Clouds. Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, Adelaide, Australia.","DOI":"10.1109\/DICTA.2015.7371262"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1007\/s00371-008-0223-2","article-title":"Spline-based feature curves from point sampled geometry","volume":"24","author":"Daniels","year":"2008","journal-title":"Vis. Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1111\/j.1467-8659.2009.01388.x","article-title":"Feature preserving point set surfaces based on non-linear kernel regression","volume":"28","author":"Oztireli","year":"2009","journal-title":"Comput. Graph. Forum"},{"key":"ref_24","first-page":"172","article-title":"Line segment extraction for large scale unorganized point clouds. ISPRS-J. Photogramm","volume":"102","author":"Lin","year":"2015","journal-title":"Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.cad.2014.11.004","article-title":"Outlier detection for scanned point clouds using majority voting","volume":"62","author":"Wang","year":"2015","journal-title":"Comput.-Aided Des."},{"key":"ref_26","unstructured":"Feng, C., Taguchi, Y., and Kamat, V.R. (June, January 31). Fast Plane Extraction in Organized Point Clouds Using Agglomerative Hierarchical Clustering. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Lu, W., Zeng, M.J., Wang, L., Luo, H., Mukherjee, S., Huang, X.H., and Deng, Y.M. (2019). Navigation algorithm based on the boundary line of tillage soil combined with guided filtering and improved anti-noise morphology. Sensors, 19.","DOI":"10.20944\/preprints201908.0282.v1"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4093","DOI":"10.1109\/JSEN.2019.2899034","article-title":"A novel method of the Brillouin gain spectrum recognition using enhanced Sobel operators based on BOTDA system","volume":"19","author":"Li","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s11128-019-2376-5","article-title":"Quantum image edge extraction based on improved Prewitt operator","volume":"18","author":"Zhou","year":"2019","journal-title":"Quantum Inf. Process."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2018\/3598284","article-title":"Implementing a parallel image edge detection algorithm based on the Otsu-Canny operator on the hadoop platform","volume":"3","author":"Cao","year":"2018","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.compag.2018.11.008","article-title":"Multi-sensor based attitude prediction for agricultural vehicles","volume":"156","author":"Zhu","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1177\/0278364913478897","article-title":"The Canadian planetary emulation terrain 3d mapping dataset","volume":"32","author":"Tong","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1177\/0278364919841437","article-title":"The Rosario dataset: Multisensor data for localization and mapping in agricultural environments","volume":"38","author":"Pire","year":"2019","journal-title":"Int. J. Robot. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s10846-017-0495-8","article-title":"Planning stable and efficient paths for reconfigurable robots on uneven terrain","volume":"87","author":"Norouzi","year":"2017","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s10514-015-9474-8","article-title":"Probabilistic stable motion planning with stability uncertainty for articulated vehicles on challenging terrains","volume":"40","author":"Norouzi","year":"2016","journal-title":"Auton. Robot."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhu, Q.Y., Wu, J.J., Hu, H.S., Xiao, Q.S., and Chen, W. (2018). LiDAR point cloud registration for sensing and reconstruction of unstructured terrain. Appl. 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