The integration of equipment and other devices built into industrial robot cells with modern Ethernet interface technologies and low-cost mass produced devices (such as vision systems, laser scanners, force torque-sensors, PLCs and PDAs etc.) enables integrators to offer more powerful and smarter solutions. Nevertheless, the programming of all these devices efficiently requires very specific knowledge about them, such as their hardware architectures and specific programming languages as well as details about the system's low level communication protocols.To address these issues, this paper describes and analyses the Plug-and-Play architecture. This is one of the most interesting service-oriented architectures (SOAs) available, which exhibits characteristics that are well adapted to industrial robotics cells. To validate their programming features and applicability, a test bed was specially designed. This provides a new graphical service orchestration which was implemented using Workflow Foundation 4 of .NET. The obtained results allowed us to verify that the use of integration schemes based on SOAs reduces the system integration time and is better adapted to industrial robotic cell system integrators.
A method for computing the distance between two moving robots or between a mobile robot and a dynamic obstacle with linear or arc‐like motions and with constant accelerations is presented in this paper. This distance is obtained without stepping or discretizing the motions of the robots or obstacles. The robots and obstacles are modelled by convex hulls. This technique obtains the future instant in time when two moving objects will be at their minimum translational distance ‐ i.e., at their minimum separation or maximum penetration (if they will collide). This distance and the future instant in time are computed in parallel. This method is intended to be run each time new information from the world is received and, consequently, it can be used for generating collision‐free trajectories for non‐holonomic mobile robots
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.