Mobile Teach & Repeat

Mobile Teach & Repeat

RUVU’s Mobile Teach & Repeat software application is the fastest and easiest way to automate any logistic task. The user simply records a path once and the robot can operate autonomously the next round.

Even in crowded or messy environments without any infrastructure, our software will drive your robot safely and reliably. Especially when used in combination with sensor technology by Accerion.

For a large US-based postal service company, RUVU successfully integrated their Mobile Teach & Repeat software on a Husky mobile robot from Clearpath Robotics.

This works on your AGV or mobile robot too! Contact us to request a demo.

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Autonomous navigation for inspection robots

Autonomous navigation for inspection robots

For ExRobotics, we integrated our navigation software on their ExR-1 robot. This enabled the robot to navigate a tank farm completely autonomously. The functionality was tested and demonstrated at an actual tank farm in Pernis.

Iwan de Waard (ExRobotics): “With RUVU, we were able to make our robot autonomous in only a few months time. Fantastic to see that RUVU is able to transfer the latest in scientific knowledge to a real-world application.”

The ExR-1 uses Swift Navigation‘s GPS-RTK system to determine its position at centimeter level. This enables an operator to define a precise route for the robot to follow, or use geofencing to make sure the robot stays within a specified area. An XSens IMU was added to estimate the pose of the robot, so it can climb and descend slopes. Finally, an Intel RealSense depth camera is used for environment perception. This way, the robot can avoid driving into objects, people, or off cliffs. The RUVU navigation software allows for smooth navigation along the route, operator intervention and teleoperation, navigation to custom goals, and obstacle avoidance.

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Vision guided pick and place demo

Vision guided pick and place demo

6-DOF Robotic arm application where objects are picked from one conveyor belt and placed on another. The set-up is dynamic in the sense that the objects are played arbitrarily on the conveyor belt. The vision systems detects the objects, the robot dynamically calculates a collision free trajectory to pick and place the objects.

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