Pallet detection is the key step of cargo handling for warehouse robots. A pallet detection method based on point clouds plane contour matching is proposed to solve the current detection method problems that are not robust to illumination and relative position between the pallet and sensor. Point clouds generated by time-of-flight (ToF) camera are filtered and segmented to different planes using region-growing method constrained by surface normal. Then point clouds are projected to the grid image along the plane’s principle normal direction. Fusion contour feature of Hu moment invariants and scale feature extracted from grid image contour is applied for similarity matching between the target and template pallet contour. The experimental results show that the method has high recognition rate and strong robustness under the circumstance of complex illumination, uncertain distance and relative pose between the pallet and sensor.
WU Wenhan,YANG Ming,WANG Bing,WANG Chunxiang
. Pallet Detection Based on Contour Matching for Warehouse Robots[J]. Journal of Shanghai Jiaotong University, 2019
, 53(2)
: 197
-202
.
DOI: 10.16183/j.cnki.jsjtu.2019.02.010
［1］CUI G Z, LU L S, HE Z D, et al. A robust autonomous mobile forklift pallet recognition［C］//International Asia Conference on Informatics in Control, Automation and Robotics. Wuhan, China: IEEE, 2010: 286-290.
［2］CHEN G, PENG R, WANG Z, et al. Pallet red localization method for vision guided forklift［C］//2012 8th International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, China: IEEE, 2012: 1-4.
［3］SEELINGER M, YODER J D. Automatic pallet engagment by a vision guided forklift［C］//IEEE International Conference on Robotics and Automation. Orlando, USA: IEEE, 2006: 4068-4073.
［4］SYU J L, LI H T, CHIANG J S, et al. A computer vision assisted system for autonomous forklift vehicles in real factory environment［J］. Multimedia Tools and Applications, 2017, 76(18): 18387-18407.
［5］VARGA R, NEDEVSCHI S. Vision-based autonomous load handling for automated guided vehicles［C］//IEEE International Conference on Intelligent Computer Communication and Processing. Santa Clara, USA: IEEE, 2014: 239-244.
［6］VARGA R, COSTEA A, NEDEVSCHI S. Improved autonomous load handling with stereo cameras［C］//IEEE International Conference on Intelligent Computer Communication and Processing. Cluj-Napoca, Romania: IEEE, 2015: 251-256.
［7］VARGA R, NEDEVSCHI S. Robust pallet detection for automated logistics operations［C］//International Conference on Computer Vision Theory and Applications. Rome, Italy: SciTePress, 2016: 470-477.
［8］BAGLIVO L. Pallet pose estimation with LIDAR and vision for autonomous forklifts［J］. IFAC Proceedings Volumes, 2009, 42(4): 612-617.
［9］BAGLIVO L, BIASI N, BIRAL F, et al. Autonomous pallet localization and picking for industrial forklifts: A robust range and look method［J］. Mea-surement Science & Technology, 2011, 22(8): 1312-1327.
［10］HU M. Visual pattern recognition by moment invariants［J］. Information Theory Ire Transactions on, 1962, 8(2): 179-187.
［11］李宝顺, 岑红燕, 包亚萍, 等. 基于平面提取的点云数据分割算法［J］. 计算机应用与软件, 2014, 31(7): 145-148.
LI Baoshun, CEN Hongyan, BAO Yaping, et al. Segmentation algorithm for point cloud data based on plane extraction［J］. Computer Application and Software, 2014, 31(7): 145-148.
