High-torque motors from Midwest Motion Products Co. help this Ordnance Disposal Robot transport bombs to safe locations where they can be disarmed.

An Ordnance Disposal Robot (ODR) is being used in Iraq to secure and transport hazardous, dangerous, or suspicious materials to places where they can be safely disarmed or destroyed.

The ODR is compact and portable, so it can fit in the trunk of a car or the storage space of a helicopter. The multiaxis remote-controlled robot has a twin-track design, enabling it to traverse nearly any terrain, including city curbs and steep sidewalks. It can even climb stairs up to an angle of 40°.

When it comes to motion control and propulsion, the robot relies on 24-Vdc electric gearmotors from Midwest Motion Products Co., Watertown, Minn. The gearmotors provide the motion for the shoulder-rotate axis, as well as the main drive units that power the twin tracks. The shoulder-axis motor incorporates planetary gearing, and measures less than 2 in. (diameter) by 6 in. (length). Despite its compact size, the gearmotor can deliver up to 78 lb-in. of torque at output shaft speeds of 70 rpm.

DeviceNet reorganization

ODVA has reorganized its DeviceNet specification, as well as released several specification enhancements for DeviceNet and EtherNet/IP.

Under the new organization, the Common Industrial Protocol (CIP), which is used by all CIP networks, will be defined in one volume, while the specific network adaptations of CIP will be covered in separate volumes. CIP — which is managed jointly by ODVA and ControlNet International — allows complete integration of control with information and Internet technologies. It provides seamless communication from the plant floor through the enterprise, combined with scalable network architecture, and allows companies to integrate I/O control, device configuration, and data collection across multiple networks.

Available developments to the CIP, DeviceNet, and EtherNet/IP specifications include new encoder capabilities, device self-documentation, QuickConnect over DeviceNet, new semiconductor-industryrelated enhancements, M12 connector option for EtherNet/IP, and increased flexibility to configure the data link layer of EtherNet/IP.

Design process gets framed

Researchers at Rensselaer Polytechnic Institute and the University of Pennsylvania have developed a new framework to support the design of automated manufacturing and robotic systems.

Sponsored by the National Science Foundation, researchers at Rensselaer Polytechnic Institute and the University of Pennsylvania have developed a new framework to support the design of automated manufacturing and robotic systems used for such purposes as assembly, part feeding, and material handling. The framework can also be used to design and control robots to do a variety of jobs that humans can’t or that pose undue risks.

“Previously, designers of automated manufacturing and robotic systems developed prototypes using intuition gained by trial and error. With the new framework, designers have a precise set of guides to use in prototyping and refining automated manufacturing systems and robotic devices,” says Jeff Trinkle, professor and chairman of the Rensselaer Dept. of Computer Science.

The framework uses differential equations and inequalities to predict the results of actions. “For example, if a robot pushes against a box on the floor, we should be able to predict if the box will stick, slide, or tumble. The framework allows us to make such predictions so that we can now think about designing a series of actions to accomplish a specific goal,” said Trinkle.

Trinkle worked to develop the framework with Jong- Shi Pang, professor of Applied Mathematics at Rensselaer; Vijay Kumar, applied sciences professor at the University of Pennsylvania School of Engineering; and Peng Song, postdoctoral research fellow at the University of Pennsylvania.

Free machine-vision seminars

Cognex Corp., Natick, Mass., hosts free machine-vision seminars called Understanding and Applying Machine Vision Sensors. The half-day events demonstrate how vision sensors perform automated inspection tasks in the automotive, medical, pharmaceutical, food and beverage, consumer products, and electronics industries.

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