RUVU navCore as BlueBotics replacement

Rokus Ottervanger February 26, 2021 Mobile robots, Motion planning, Path planning 0 Comments

RUVU navCore as BlueBotics replacement

In just a few days, RUVU built a drop-in replacement for BlueBotics’ ANT lite+. It uses RUVU’s ROS based navCore for localization and autonomous navigation. Also, it uses RUVU’s fleetCore plans the routes and schedules the navigation tasks.
This can be done with any mobile robot or AGV!

This project was partially funded by
– OPZuid
– Provincie Limburg
– Provincie Noord-Brabant
– Ministerie van Economische Zaken en Kilmaat
– EU European fund for regional development

Mobile Teach & Repeat

Rokus Ottervanger August 5, 2019 Mobile robots, Path planning, Sensor fusion 0 Comments

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.

Fleet Manager

Rokus Ottervanger January 15, 2019 Digital twin, Fleet management, Multi-robot, Path planning, Simulation 0 Comments

Fleet Manager

The RUVU Fleet Manager is capable of assigning the best robots to the right jobs, planning optimal routes, scheduling complex jobs and much more. Let us know what you would want to do with it using the button below.

Autonomous navigation for inspection robots

Rokus Ottervanger October 24, 2018 3d vision, Environment modeling, Mobile robots, Motion planning, Sensor fusion 0 Comments

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.

Vision guided pick and place demo

Rokus Ottervanger April 4, 2018 Computer vision, Digital twin, Motion planning, Robot arm, Simulation 0 Comments

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.

Perception for autonomous driving

Rokus Ottervanger March 19, 2014 Autonomous driving, Computer vision 0 Comments

Perception for autonomous driving

The goal of the project was creating an environmental model for autonomous cars that could be used in application such as lane keeping assist or adaptive cruise control. The designed and implemented world model could fuse information of various sensor sources such as lidar, radar and camera.

Motion planning for mobile robots

Rokus Ottervanger March 19, 2014 Mobile robots, Motion planning 0 Comments

Motion planning for mobile robots

Design of a world model, planning representation and motion planner for a mobile robot that can operate in domestic environments. Reference velocities for the mobile robot platform are generated using a model predictive controller with a grid environmental model.

Robotic arm control

Rokus Ottervanger March 15, 2014 Robot arm, Simulation 0 Comments

Robotic arm control

Control of a 6DOF (degree of freedom) robotic arm that follows a varying trajectory based on an end-effector sensor. Most of the application development was initially performed with use of a simulator that exactly mimics the interfaces of the real robot arm including sensors.

Multi-robot distributed control

Rokus Ottervanger March 15, 2014 Motion control, Multi-robot 0 Comments

Multi-robot distributed control

In a multi-robot application with limited communication, a control solution was designed and implemented to distribute the robots optimally over a designated space. The solution is flexible in the sense that robots can be added and removed on the fly and without a central point of failure.

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