https://cps.unileoben.ac.at/wp/UnitreeGO1_firststeops_at_CPS.mov

The video shows our Unitree GO1 robot at its first steps at CPS. This quadruped robot can locomote in rough terrain, autonomously avoids obstacles like stones or blocking barriers, and provides a large number of sensors for navigation and mapping research projects. 

Links

• For more information about the Unitree company and the robots, visit their website at: https://m.unitree.com/products/go1/

Videos

• Research videos using the robot will be presented here. 

Publications

• Publications about the robot as well as related topics will be found here.

Picture Source: https://www.universal-robots.com [visited at 20.07.2022]

The UR3e from Universal Robots is an ultra-light, compact, collaborative table-top robot that can effortlessly perform high-precision assembly and screwdriving tasks, for example. It has a reach of 500 mm and can carry up to 3 kg of weight.

Links

• For more information about the Universal Robots company and the robots they build, visit their website at: https://www.fanuc.eu/uk/en

Videos

• Research videos using the robot will be presented here. 

Publications

• Publications about the robot as well as related topics will be found here.

The FANUC CRX-10iA robot is a six-axis robot that has a reach of 1249 mm and can carry up to 10 kg of weight. The reliability and sensitive touch detection allows the CRX-10iA to work safely alongside humans in a variety of industrial and manufacturing tasks.

Links

• Details on the FANUC CRX-10iA can be found here: https://www.fanuc.eu/~/media/files/pdf/products/robots/robots-datasheets-de/crx/crx-10ia-de.pdf?la=de
• For more information about the Fancu company and the robots they build, visit their website at: https://www.fanuc.eu/uk/en

Videos

• Research videos using the robot will be presented here. 

Publications

• Publications about the robot as well as related topics will be found here.

CPS presents a guide to build an open-source modular mobile platform for research, navigation and logistics applications. Its design leveraged off-the-shelf (OTS) components, additive manufacturing technologies, aluminium profiles, and consumable hover-board high-torque brushless direct current (BLDC) motors. It is compatible with the robot operating system (ROS) with a maximum payload of 90kg.

It provides a simple yet robust framework for contextualising simultaneous localisation and mapping (SLAM) algorithms, which are the fundamental prerequisites for autonomous navigating robots. It features several control approaches such as remote control from RC devices, Android-based devices, hand gestures, ROS rqt etc.

Components

Sensors:

• RPLIDAR A2 M8

• RealSense Depth Camera D435i

• Intel Realsense Tracking Camera T265

• Turnigy 9X 2,4 GHz 8CH Receiver (V2)

Power Supply:

• VARTA Slim Power Bank – 18000 mAh

• 36V Lithium-ion battery 4400mAh

Electronics:

• 2 x 6,5“  hoverboard brushless DC (BLDC) motors with 15 pole pairs

• Nvidia Jetson Nano B01 64GB

• Arduino Mega 2650 Rev3

• ODRIVE 56V V3.6

Videos

Publications

More information can be found in the publication: https://doi.org/10.1016/j.ohx.2023.e00426

Links

• Related Bachelor Thesis: Gesture Based Mobile Robot Teleoperation for Navigation Application

• All the design, construction and software files are freely available online under the GNU GPL v3 license at https://doi.org/10.17605/OSF.IO/K83X7

The RMP Lite 220 is a highly adaptable robot which can be used for different scenarios like f.e. indoor/outdoor delivery, patrolling, service, cleaning, AFV (warehouse), or other special applications.

Links

• Details on the RMP Lite 220 can be found here: https://segwayrobotics.wpengine.com/wp-content/uploads/2021/04/Segway-RMP-220Lite-Specs.pdf

• For more information about the Segway Robotics company and the robots they build, visit their website at: https://robotics.segway.com/

Videos

• Research videos using the robot will be presented here. 

Publications

• Publications about the robot as well as related topics will be found here.

LEGO EV3 for Robotic Tasks

We have five EV3 sets and use them for studying robot control, motion planning and visual navigation from depth images. 

We use our GitHup LEGO Python project for our developments. 

Tactile Sensing

Several special purpose sensors including depth image cameras (shown in the center in the image), IMUs, accelerometers, gyroscopes, sonic sensors (two are shown in the image), etc. can be connected to the EV3 brick. 

The EV3 systems can be used to explore neural sensor fusion approaches, embedded computing implementations and classical mobile robotics tasks.  

• Details to our LEGO Python GitHub project

Videos

https://vimeo.com/501651310https://vimeo.com/374166607

Human-inspired, Adult-size Dexterous Robot Hand

We use a adult-sized robot hand for learning grasping and object manipulation skills. The hand is mounted on our FRANKA EMIKA Panda robot. 

The hand has 19 degrees-of-freedom and uses 8 smart actuators for precise control (actuators contained inside the unit).

Under actuated design aims to provide the right balance between fine control and conformance to the shape of the objects.

Tactile Sensing

All actuators provide real time control and feedback of position, speed and current measurement (with direction), enabling inference of applied force.

Additional data including actuator temperature, (over)load status and PWM, a Palm ToF Distance sensor and optional Capacitive pads at the back of the palm complete the sensor array.

We also have five 3-axis force-torque sensors (FTS) (shown in the image) attached to each finger tip. The FTS measure contact force and shear forces with a resolution of 1mN / 0.1g.

• E-Manual of the RH8 hand.
• ROS Interface description of the RH8 hand.
• E-Manual of the 3Axis F/T Sensors 
• Details to our FRANKA ROS GitHub project.
• Details on the robot hardware can be found on the SEED Robotics page.

Videos

• Research videos using the robot will be presented here. 

Publications

2020

Xue, H.; Boettger, S.; Rottmann, N.; Pandya, H.; Bruder, R.; Neumann, G.; Schweikard, A.; Rueckert, E. Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks Proceedings Article In: International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2020), 2020. Links | BibTeX @inproceedings{Xue2020, title = {Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks}, author = {H. Xue and S. Boettger and N. Rottmann and H. Pandya and R. Bruder and G. Neumann and A. Schweikard and E. Rueckert}, url = {https://cps.unileoben.ac.at/wp/ASPAI2020Xue.pdf, Article File}, year = {2020}, date = {2020-06-30}, booktitle = {International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2020)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Close Article File Close

FRANKA EMIKA’s Panda robot arm is a complient, light-weight robot arm with seven degrees-of-freedom. 

We use the C++ libfranka library in our own ROS project for learning complex manipulation skills. 

Links

• Details to our FRANKA ROS GitHub project
• Details on the robot hardware can be found on the FRANKA EMIKA page
• Or on the developer site on world.franka.de

Videos

• Research videos using the robot will be presented here. 

Publications

2020

Xue, H.; Boettger, S.; Rottmann, N.; Pandya, H.; Bruder, R.; Neumann, G.; Schweikard, A.; Rueckert, E. Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks Proceedings Article In: International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2020), 2020. Links | BibTeX @inproceedings{Xue2020, title = {Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks}, author = {H. Xue and S. Boettger and N. Rottmann and H. Pandya and R. Bruder and G. Neumann and A. Schweikard and E. Rueckert}, url = {https://cps.unileoben.ac.at/wp/ASPAI2020Xue.pdf, Article File}, year = {2020}, date = {2020-06-30}, booktitle = {International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2020)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Close Article File Close