New Cornell Research On Object Identification Within Enviroments

In Cornell's Personal Robotics Laboratory, a team led by Ashutosh Saxena, assistant professor of computer science, is teaching robots to manipulate objects and find their way around in new environments. The researchers trained a robot by giving it 24 office scenes and 28 home scenes in which they had labeled most objects. The computer examines such features as color, texture and what is nearby and decides what characteristics all objects with the same label have in common. In a new environment, it compares each segment of its scan with the objects in its memory and chooses the ones with the best fit.

 

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ST Robotics Develops the Workspace Sentry for Collaborative Robotics

ST Robotics Develops the Workspace Sentry for Collaborative Robotics

The ST Robotics Workspace Sentry robot and area safety system are based on a small module that sends an infrared beam across the workspace. If the user puts his hand (or any other object) in the workspace, the robot stops using programmable emergency deceleration. Each module has three beams at different angles and the distance a beam reaches is adjustable. Two or more modules can be daisy chained to watch a wider area. "A robot that is tuned to stop on impact may not be safe. Robots where the trip torque can be set at low thresholds are too slow for any practical industrial application. The best system is where the work area has proximity detectors so the robot stops before impact and that is the approach ST Robotics has taken," states President and CEO of ST Robotics David Sands.