Development of a SCARA robot arm for palletizing applications based on computer vision

This paper develops a computer vision system integrated with a SCARA robot arm to pick and place objects. A novel method to calculate the 3D coordinates of the objects from a camera is proposed. This method helps simplify the camera calibration process. It requires no knowledge of camera modeling and mathematical knowledge of coordinate transformations. The least square method will predate the Equation describing the relationship between pixel coordinates and 3D coordinates. An image processing algorithm is presented to detect objects by color or pixel intensity (thresholding method). The pixel coordinates of the objects are then converted to 3D coordinates. The inverse kinematic Equation is applied to find the joint angles of the SCARA robot. A palletizing application is implemented to test the accuracy of the proposed method. The kinematic Equation of the robot arm is presented to convert the 3D position of the objects to the robot joint angles. So, the robot moves exactly to the required positions by providing suitable rotational movements for each robot joint. The experiment results show that the robot can pick and place 27 boxes on the conveyor to the pallet with an average time of 2.8s per box. The positions of the boxes were determined with an average error of 0.5112mm and 0.6838mm in the X and Y directions, respectively

A review of unilateral grippers for meat industry automation

With the expectation that meat consumption will grow by 12% over the next decade, coupled with the reported labour issues and viruses attacking human and animal health, there is a growing requirement for red meat slaughterhouse automation. Changes to current abattoir setups and processes are necessary to realise for sustainable, low-cost and scalable automation. However, to achieve such autonomous nirvana, simple, cost-efficient and robust tooling to support these systems are sought. This includes grippers used to hold, manipulate and transport workpieces, such as primal cuts of red meat, for example, with the simplest type being unilateral gripping systems. Scope and approach This paper critically reviews various unilateral gripping solutions available in cross-industry sectors or developed in research that could be used or adapted for the meat industry. Criteria for such tooling are simplicity, low-cost, durability and robustness, whilst being capable of gripping highly deformable objects of various structures and maintaining safety and hygiene standards. The focus is on air-driven grippers due to their ability to hold high payloads without causing visual and physical damage to the product. Key findings and conclusions Three pneumatic-based unilateral gripper principles, namely Coanda, Bernoulli and Vacuum, are critically reviewed for their feasibility in meat industry automation. In conclusion, the simple vacuum-based system offers the best solution of holding force and low damage thresholds. However, vacuum based design and adaption requires thought for meat surface and structure variance. This will inevitably lead to future experimental research and development work.A review of unilateral grippers for meat industry automationpublishedVersio

The impact of disruptive technology on the manufacturing process, and productivity, in an advanced manufacturing environment.

Doctoral Degree. University of KwaZulu-Natal, Durban.Disruptive technology plays a critical role in the performance of mechatronic systems in an advanced manufacturing environment. Robots were used to perform pick and place task in a virtual manufacturing environment. Newton-Raphson model, renewal theorem and queuing theory were used to model the disruptive technology and develop decision-making algorithms in an advanced process. The motion of the conveyor belt system starved modeled and simulated to determine suitable design parameters that were compatible with the tasks of the pick and place robot. MATLAB and Engineering Equation Solver (EES) were used to determine static solutions and simulated solutions to the pick and place problem in the advanced manufacturing process. The results from the simulations were used to develop suitable task-dependent operational conditions in the advanced manufacturing environment. The simulation results were used to determine the optimal conveyor speeds required for the robotic tasks. Comparing the throughput rate of the developed system with the simulated system indicated that optimal productivity was achieved when the decision-making algorithms were implemented at the early stages of the manufacturing process