Robot manufacturers claim to have a given accuracy and repeatability. Although, all of these specifications can only work when a proper calibration has been done on the robot. The calibration process for industrial robots is composed of four main steps:
Emerging Applications in Robotic Industrial and Service Blog
We recently release an article on ''What is a Force-Torque Sensor''. Now that you know what a FT sensor is, we thought that you might be interested in the basics of how these devices work.
Programming a robotic welding cell has never been easier with our newest How–to video showing Kinetiq Teaching, a new technology to quickly and easily task welding robots without requiring in-depth programming knowledge. This visual approach takes you step by step through the programming of a linear welding path for welding automation.
Both of our Adaptive Grippers are able to grip objects of various shapes using their innovative finger mechanism. This allows for firm grips of various objects without the need to build custom grippers for each application. In addition to this adaptability, the Gripper is able to determine when it has gripped an object. This is useful to determine if the pick-up procedure was performed correctly and if the robot can move to the next step of its program. In some cases, however, it is also useful to verify if the Gripper still has the object after a motion is executed by the robot. For example, if the object position was not initially determined accurately (for instance, if the object has moved or if the vision system had a problem), it is possible that the object could be picked up in an awkward position. In this situation, the object might slip out of the Gripper if the robot moves very rapidly to its next position. Knowing that the object was dropped is crucial for many applications. So below, I will explain the appropriate procedure to verify if the Adaptive Gripper still has the object after a robot motion.
How the object is detected during the grip
When a command is sent to close the fingers of the Gripper, the motor moves towards a target position. If the motion is stopped because the Gripper has found an object, the force applied by the fingers will increase until the current sent to the motor exceeds its limit (which is fixed using the force parameter). At that moment, the motor will stop moving and the grip force will be maintained by the Gripper's auto-locking mechanism. By reading the motor position, the Gripper is able to determine if an object was gripped or if the motion was stopped due to the fingers touching themselves. However, from that moment, the Gripper will consider that the object is gripped and will not detect an object loss unless the procedure explained in the next section is executed.
This article explores how feedback from the 2-Finger Adaptive Gripper might be used in industrial applications.
As explained in a previous article, the 2-Finger Adaptive Robot Gripper is able to achieve both pinching and encompassing grips by automatically conforming to the shape of the object. The Gripper is therefore simply programmed using straightforward open/close commands (everything else is taken care by the Gripper controller and the patent pending finger mechanism). In today's article, we'll take a look at how the Gripper can be controlled: how to communicate with it, how to perform simple actions, how to adapt its behavior and how to test the different commands.
When watching how the 2-Finger Adaptive Robot Gripper works in the following video you might ask yourself; how this Gripper can be so versatile while using only one actuator? The secret lies in its unique mechanical architecture.
Topics: industrial robotics, robot gripper, robotics how to, adaptive gripper, robotic gripper, electric gripper, Robotiq, 2-finger gripper, mechanical intelligence, robot, servo electric gripper, underactuation
This article presents an overview on how a servo-electric gripper works. The image below shows the main components of an electric gripper and how it interfaces with a robot.
Today's industrial robots are almost always programmed using a position control scheme. Typically, the robot tool follows a prescribed trajectory in space which has been pre-programmed or "teached" before run-time. Sometimes, the robot gets its reference position from a vision system, which enables it to adapt its motion to its changing environment. However, for some applications, it is more important to precisely control the force applied by the end-effector rather than controling the robots positioning. One example of this is the finishing of a machined part, as seen in the video below: