A PLC Controlled Pick and Place Pneumatic Arm Brace for Automatic Manufacturing Systems

Programmable Logic Controllers (PLCs) are specialized computers used for the control and operation of manufacturing process and machinery, especially in industrial environment. PLC is a user friendly, microprocessor-based specialized computer that carries out control functions of many types and levels complexity that cannot be done by human. This project employees a 9-step problem solving approach to develop a PLC controlled pick and place pneumatic arm brace for automatic manufacturing system in order to solve the problem which appears in a production line. It includes the following steps: define the process operation and list the step-by-step sequence of operation, define and list the input and output devices and sensors required for proper operation, assign corresponding PLC scheme, draw up the PLC scheme, enter the program into the PLC, check the program by using the function mode, wire the PLC system to a simulator and check for hidden safety defects or sequencing problems, check the actual process and make modifications as required. The result shows that the PLC system has been set up and worked properly in the laboratory floor

Pick and Place Without Geometric Object Models

We propose a novel formulation of robotic pick and place as a deep reinforcement learning (RL) problem. Whereas most deep RL approaches to robotic manipulation frame the problem in terms of low level states and actions, we propose a more abstract formulation. In this formulation, actions are target reach poses for the hand and states are a history of such reaches. We show this approach can solve a challenging class of pick-place and regrasping problems where the exact geometry of the objects to be handled is unknown. The only information our method requires is: 1) the sensor perception available to the robot at test time; 2) prior knowledge of the general class of objects for which the system was trained. We evaluate our method using objects belonging to two different categories, mugs and bottles, both in simulation and on real hardware. Results show a major improvement relative to a shape primitives baseline

Pick-And-Place Mobile Autonomous Robots

This thesis presents a Research and Development study on building Pick-and-Place Mobile Autonomous Robot (MARS). It considers various steps and criteria during the study. This project is mainly regarding on designing and fabricating an autonomous robot which posses the functions such as line tracking, sense section radius of the Canister, feed in the Rubber Balls, etc. This robot is designed (in the size of 500mm x 500mm x 1500mm before the game start and limited 2000mm in height after the game start) to accomplish tasks which are tracks through the game field, reaches the Main Torch, rotates the Main Torch and finally feed the Rubber Balls into the Canister. By applying Quality Function Deployment (QFD), robot was successfully designed from the several alternatives. It was designed to be detachable to form two robots named as EX-Transporter and Feeder-EX. According to their tasks, control systems were built to enhance the efficiency of the robots. However, several tests were conducted to ensure their reliability, such as tracking test, straightness test, robot stabilizing system test, defending system test, robot extending system test, radius sensing system test and Rubber Balls feeding system test. As a result, these robots achieve a good performance through the tests. However, it is recommended that, elastic strings which were used to replace the complex mechanism needed to be changed after three times of usage to ensure its functionality

Optical Pick and Place Machine

The current market does not contain a low-cost machine capable of building optical surface mounted devices (SMDs). This project attempts to design a machine capable of handling optical parts which are highly sensitive components that rely on accurate placement. The machine will be a mixture of existing technology and specifically designed parts. This machine was designed around a Computer Numeric Control (CNC) machine frame (OpenBuilds). A controller conducts all actions performed by the machine. These actions include motion along x-, y-, and z-axes along with rotational motion. There is also a dual-camera subsystem which helps the user to determine ideal optical part placement. The machine is reprogrammable by using opensource software. Overall, it will provide optical SMD design capability to a larger population by decreasing the cost of such a machine

An approach for smooth trajectory planning of high-speed pick-and-place parallel robots using quintic B-splines

This paper presents a new, highly effective approach for optimal smooth trajectory planning of high-speed pick-and-place parallel robots. The pick-and-place path is decomposed into two orthogonal coordinate axes in the Cartesian space and quintic B-spline curves are used to generate the motion profile along each axis for achieving C4-continuity. By using symmetrical properties of the geometric path defined, the proposed motion profile becomes essentially dominated by two key factors, representing the ratios of the time intervals for the end-effector to move from the initial point to the adjacent virtual and/or the via-points on the path. These two factors can then be determined by maximizing a weighted sum of two normalized single-objective functions and expressed by curve fitting as functions of the width/height ratio of the pick-and-place path, so allowing them to be stored in a look-up table to enable real-time implementation. Experimental results on a 4-DOF SCARA type parallel robot show that the residual vibration of the end-effector can be substantially reduced thanks to the very continuous and smooth joint torques obtained

Leveraging Symmetries in Pick and Place

Robotic pick and place tasks are symmetric under translations and rotations of both the object to be picked and the desired place pose. For example, if the pick object is rotated or translated, then the optimal pick action should also rotate or translate. The same is true for the place pose; if the desired place pose changes, then the place action should also transform accordingly. A recently proposed pick and place framework known as Transporter Net captures some of these symmetries, but not all. This paper analytically studies the symmetries present in planar robotic pick and place and proposes a method of incorporating equivariant neural models into Transporter Net in a way that captures all symmetries. The new model, which we call Equivariant Transporter Net, is equivariant to both pick and place symmetries and can immediately generalize pick and place knowledge to different pick and place poses. We evaluate the new model empirically and show that it is much more sample efficient than the non-symmetric version, resulting in a system that can imitate demonstrated pick and place behavior using very few human demonstrations on a variety of imitation learning tasks.Comment: arXiv admin note: substantial text overlap with arXiv:2202.0940

Blending in pick and place applications

At the start of this internship a conventional pick and place algorithm was available to generate pick and place trajectories. To get a small motion time, time optimal point to points are constructed on the linear segments using the theory of Lambrechts, which was extended by van Dijk, while monitoring Cartesian constraints on velocity, acceleration and jerk using the procedure described by Macfarlane. The major disadvantage of this conventional algorithm is the use of a blend function during blending. On of the boundary conditions of this fixed blend function is, that the track velocity at the beginning of the blend should be equal to the track velocity at the end of the blend, i.e. no track acceleration can be attained during blending. When an application needs trajectories containing small linear segments with large blends, the manipulator must maintain that low velocity reached at the end of such a small segment during the whole blend path and this will cause more process time than necessary. In this report, a new blending algorithm is developed, which can have track acceleration during blend-ing. In this case, the manipulator can accelerate during blending and this will decrease motion time. Theoretical results prove that the generated motion time will be in fact the time optimal one. With this new pick and place algorithm simulations with different trajectories are performed an