Vision-Based Intelligent Perceiving and Planning System of a 7-DoF Collaborative Robot.

Journal: Computational intelligence and neuroscience
Published Date:

Abstract

In this paper, an intelligent perceiving and planning system based on deep learning is proposed for a collaborative robot consisting of a 7-DoF (7-degree-of-freedom) manipulator, a three-finger robot hand, and a vision system, known as IPPS (intelligent perceiving and planning system). The lack of intelligence has been limiting the application of collaborative robots for a long time. A system to realize "eye-brain-hand" process is crucial for the true intelligence of robots. In this research, a more stable and accurate perceiving process was proposed. A well-designed camera system as the vision system and a new hand tracking method were proposed for operation perceiving and recording set establishment to improve the applicability. A visual process was designed to improve the accuracy of environment perceiving. Besides, a faster and more precise planning process was proposed. Deep learning based on a new CNN (convolution neural network) was designed to realize intelligent grasping planning for robot hand. A new trajectory planning method of the manipulator was proposed to improve efficiency. The performance of the IPPS was tested with simulations and experiments in a real environment. The results show that IPPS could effectively realize intelligent perceiving and planning for the robot, which could realize higher intelligence and great applicability for collaborative robots.

Authors

  • Linfeng Xu
    Department of Mechanical & Aerospace Engineering, University of Florida, Gainesville 32611, FL, USA.
  • Gang Li
    The Centre for Cyber Resilience and Trust, Deakin University, Australia.
  • Peiheng Song
    AI Robot Research Group, Peng Cheng National Laboratory, Shenzhen 518055, China.
  • Weixiang Shao
    Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60612, USA.