CloudGripper: The Open Source Cloud Robotics Testbed

Introduction

CloudGripper is an open source cloud robotics testbed for remote robotic manipulation research, benchmarking and data collection at scale at KTH Royal Institute of Technology, Stockholm, Sweden. CloudGripper v1 features 32 small robot arm cells. CloudGripper is currently being extended with an additional set of industrial arms with increased capacity for complex dexterous manipulation. The aim of the project is to create a global open source community of contributors and remote users of this testbed that will leverage CloudGripper for research, benchmarking and data collection to establish common reliable data-driven foundations for robotic manipulation and cloud robotics research.

Newsletter, Signup and Contact

You can sign up to our newsletter here. Alternatively, contact us at info (at) cloudgripper (dot) org.

IEEE ICRA 2026 Cloud Robotics Competition

We are excited to host the IEEE ICRA 2026 Cloud Manipulation Competition track which is part of the 11th Robotic Grasping and Manipulation Competition at IEEE ICRA 2026. Read more here

CloudGripper Milestones

Architecture description

Read more about CloudGripper here: "CloudGripper: An Open Source Cloud Robotics Testbed for Robotic Manipulation Research, Benchmarking and Data Collection at Scale" IEEE ICRA 2024, Muhammad Zahid and Florian T. Pokorny.

Open Software and Hardware

You can find sofware and CAD files under open source licenses on our GitHub organization: CloudGripper on GitHub. Assembly instructions are available here. A MuJoCo simulation of CloudGripper will also be made available shortly. The CloudGripper-Autograsper software can be found here together with an associated dataset here.

Large Open Datasets

We are currently finalizing the best options for hosting the large multi terabyte datasets being generated with the CloudGripper robots. At the moment two datasets of a total of approximately 2 terabytes of randomized pushing interactions are available. A data sample from the CloudGripper-Rope-100 dataset of more than 100 hours of rope pushing interactions is available here. A further datasample of our recent work "Video Transformers under Occlusion: How Physics and Background Attributes Impact Large Models for Robotic Manipulation" Shutong Jin, Ruiyu Wang, Muhammad Zahid, Florian T. Pokorny with videos of more than 1000 hours of robot-object pushing interactions can be found here.

Please email info (at) cloudgripper (dot) org for access to the full dataset and more information.

Research Projects using CloudGripper

The initial release of CloudGripper was initially developed by Muhammad Zahid and Associate Prof. Florian Pokorny at the Division of the Robotics, Perception and Learning at KTH Royal Institute of Technology. The current design features 32 small robot arm work cells and a set of industrial robot arms. CloudGripper forms the key infrastructure used for the the WASP funded Swedish excellent research environment (NEST) grant "Intelligent Cloud Robotics for Real-Time Manipulation at Scale" coordinated by Florian T. Pokorny and with co-investigators Monowar Bhuyan, Erik Elmroth and Martina Maggio. This work is partially supported by the Wallenberg AI, Autonomous Systems and Software program (WASP) funded by the Knut and Alice Wallenberg Foundation.

CloudGripper end-users & collaborators

The CloudGripper platform has been featured in events, tutorials and research collaborations with many of our partners.

We are building a community around cloud robotics. Join the community and use the system for your research!
  • Florian Pokorny, Associate Prof. KTH, CloudGripper co-initiator
  • Muhammad Zahid, Research Engineer, KTH, CloudGripper co-initiator
  • Martina Maggio, Professor, Lund University, WASP-Nest co-PI
  • Erik Elmroth, Professor, Umeå University, WASP-Nest co-PI
  • Monowar Bhuyan, Assist. Prof, Umeå University, WASP-Nest co-PI
  • Ken Goldberg, Professor, UC Berkeley
  • Kaiyuan Eric Chen, PhD student, UC Berkeley
  • Jeff Ichnowski, Assist. Prof., Carnegie Mellon University
  • Shutong Jin, PhD student, KTH
  • Ruiyu Wang, PhD student, KTH
  • Holly Dinkel, PhD student, University of Illinois at Urbana-Champaign & NASA
  • Bhumsitt “Bose” Pramuanpornsatid, Student, University of Illinois at Urbana-Champaign
  • Axel Kaliff, master student, KTH
  • Alessandro Adami, PhD student, University of Padova
  • Pietro Falco, Associate Professor, University of Padova
  • Carli Ruggero, Associate Professor, University of Padova