Automation in manufacturing has come far by using industrial robots. However, industrial robots require tremendous efforts in static calibration due to their lack of senses. Force and vision are the most useful sensing capabilities for a robot system operating in an unknown or uncalibrated environment and by integrating sensors in real-time with industrial robot controllers, dynamic processes need far less calibration which leads to reduced lead time. By using robot systems which are more dynamic and can perform complex tasks with simple instructions, the production efficiency will rise and hence also the profit for companies using them.
Although much research has been presented within the research community, current industrial robot systems have very limited support for external sensor feedback, and the state-of-the-art robots today have generally no feedback loop that can handle external force- or position controlled feedback. Where it exists, feedback at the rate of 10 Hz is considered to berare and is far from real-time control.
A new system where the feedback control can be possible within a real-time behavior, developed at Lund Institute of Technology, has been implemented. The new system for rapid feedback control is a highly complex system, possible to install in existing robot cells, and enables real-time (250 Hz) sensor feedback to the robot controller. However, the system is not yet fully developed, and a lot of issues need to be considered before it can reach the market in other than specific applications.
The implementation and deployment of the new interface at LiTH shows that the potential for this system is large, since it makes production with robots exceedingly flexible and dynamic, and the fact that the system works with real- time feedback makes industrial robots more useful in tasks for manufacturing.
Source: Linköping University
Author: Lundqvist, Rasmus | Söreling, Tobias
- Rapid Polymer Prototyping for Low Cost and Robust Micro Robots (Mechanical Project)
- Q-Learning for Robot Control (Robotics Project)
- Robust Communication for Location-Aware Mobile Robots using Motes (Computer Project)
- A Neural Network Based Brain-Computer Interface for Classification of Movement Related EEG (Mechanical Project)
- Experiments in Robot Formation Control with an Emphasis on Decentralized Control Algorithms (Mechanical Project)
- Design, Analysis, and Fabrication of a Snake-Like Robot with a Rectilinear Gait (Mechanical Project)
- A Real-Time Classification approach of a Human Brain-Computer Interface based on Movement Related Electroencephalogram (Mechanical Project)