Complex Carton Packaging with Dexterous Robot Hands
N. Venketesh, Sihao Jian
- Year
- 2006
- Citations
- 6
- Access
- Open access
Abstract
The chapter has presented a dexterous reconfigurable assembly and packaging system (D-RAPS) with dexterous robot fingers. The aim of this research was to design a reconfigurable assembly and packaging system that can handle cardboard cartons of different geometry and shapes. The initial idea was to develop such a system that can demonstrate adaptability to cartons of different styles and complexities. It was shown that the packaging machine could fold two cartons of completely different shapes. The cycle time for the folding was approximately 45 seconds in each case. Though this is not an optimized time for folding, it is envisaged to reduce the cycle time to 30 seconds or less with on-line data transfer. Although there are many issues that need to be addressed before a fully flexible machine can be realized on the shop floor, nevertheless, the research was aimed at proving the principle of quick change-over, which faces the packaging industry. The future enhancement will include optimization of finger trajectory, use of tactile sensors for force feedback to avoid excessive pressure on the panel, and astrictive mode of grasping to involve the vacuum system at the fingertips. It is also proposed to integrate the simulation model directly with the actual machine to download the motion data online. The XY-table can be motorized and controlled for autoreconfiguration. These advanced techniques will automate the entire packaging process starting from the two dimensional drawing of the cardboard, defining its kinematics then generating the motion sequences leading to the finished product packaging. It is also envisaged to mount such dexterous reconfigurable hands directly onto a robotic arm to offer higher level of flexibility in packaging, if this can be miniaturized. The system will not only perform carton folding but can also be used to insert the product into the carton during the folding sequences. This will reduce the packaging time and will also be able to meet challenges of high adaptability to ever changing demands of high-end personal product packaging.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002