A method for robotic grasping based on improved Gaussian mixture model

Author:

Tao Yong, ,Ren Fan,Chen Youdong,Wang Tianmiao,Zou Yu,Chen Chaoyong,Jiang Shan, ,

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

Reference7 articles.

1. Y. Mollard, T. Munzer, A. Baisero, M. Toussaint, M. Lopes, Robot programming from demonstration, feedback and transfer, 2015 IEEE/RSJ international conference on intelligent robots and systems (IROS), 2015. Available

2. K. Bousmalis, A. Irpan, P. Wohlhart, Y. Bai, M. Kelcey, M. Kalakrishnan, Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping, 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018. Available

3. M. Schwarz, C. Lenz, G. M. García, S. Koo, A. S. Periyasamy, M. Schreiber, Fast Object Learning and Dual-arm Coordination for Cluttered Stowing, Picking, and Packing, 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018. Available

4. P. Schmidt, N. Vahrenkamp, M. Wächter, T. Asfour, Grasping of Unknown Objects Using Deep Convolutional Neural Networks Based on Depth Images, 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018. Available

5. E. Rohmer, S. P. N. Singh, M. Freese, V-REP: A Versatile and Scalable Robot Simulation Framework, 2013 IEEE/RSJ International Conference on Intelligent Robots and System, 2013. Available

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