[COMPARE] Ecosystem Digest, June 22 - July 5, 2025

[COMPARE Ecosystem]

COMPARE Ecosystem Digest, June 22 - July 5, 2025

Here’s what you may have missed last week and what’s coming up soon!

🤖 Congratulations to the winners of the Robothon Grand Challenge!

• At this year's robotics competition, international research teams focused on a new electronic task board design focused on assessing the agility and responsiveness of their robot platforms. The tasks centered around the use of an electronic touchscreen which is a frequently replaced component in electronic waste handling and vital to the circular economy. See the competition website for more info: https://automatica-munich.com/en/munich-i/robothon/
• 1st Place: Atlabotics (8,000 EUR) of Atlantic Technological University
• 2nd Place: RoboTechX MDX (6,000 EUR) of Middlesex University Dubai
• 3rd Place: RoboPig (2,000 EUR) of Technical University of Applied Sciences Würzburg-Schweinfurt (THWS)

🤖 Latest additions to robot-manipulation.org:

• Software Components: Grasp Planners
• Summary of new additions below. See the repo for full details!

• CAPGrasp: https://github.com/wengzehang/CAPGrasp
• CAPGrasp is an R3 × SO(2)-equivariant 6-Degrees of Freedom (DoF) continuous approach-constrained generative grasp sampler. It includes a novel learning strategy for training CAPGrasp that eliminates the need to curate massive conditionally labeled datasets and a constrained grasp refinement technique that improves grasp poses while respecting the grasp approach directional constraints. 

• Edge Grasp Network: https://github.com/HaojHuang/Edge-Grasp-Network
• Edge Grasp Network is a novel method and neural network model that enables better grasp success rates relative to what is available in the literature. The method takes standard point cloud data as input and works well with single-view point clouds observed from arbitrary viewing directions.  

• EquiGraspFlow: https://github.com/bdlim99/EquiGraspFlow
• EquiGraspFlow is a flow-based SE(3)-equivariant 6-DoF grasp pose generative model that can learn complex conditional distributions on the SE(3) manifold while guaranteeing SE(3)-equivariance. Our model achieves the equivariance without relying on data augmentation, by using network architectures that guarantee it by construction. 

• ICGNet: https://github.com/renezurbruegg/icg_net
• The method uses point cloud data from a single arbitrary viewing direction as an input and generates an instance-centric representation for each partially observed object in the scene. This representation is further used for object reconstruction and grasp detection in cluttered table-top scenes. 

• Many more additions are on their way as we still digest the material presented at ICRA, CVPR, and RSS. Come across any new open-source products or benchmarking assets that should be added? Use this Google Form to let us know! https://forms.gle/LHrtmDpm82X4qrDk6
  
  

• Events: Workshops

• The COMPARE Ecosystem workshop, "Benchmarking Robot Manipulation: Improving Interoperability and Modularity," was held last week at RSS 2025! Presentation videos, slide decks, and key takeaways from breakout discussions will be posted on the website soon, so keep an eye out!
    
  
  

• Have suggestions for events we should add? Use this Google Form to let us know! https://forms.gle/PfiSRjcuQnavbPNS9

🤖 What's coming up soon?

• Ubiquitous Robots (UR) 2025 is this week! College Station, TX, USA, June 30 - July 2, 2025
  
  

• Monday, June 30, 2025
• Virtual Environment-Based Synthetic Data Generation for Robotic Training
• Symbiosis or Separation? Revisiting the Interface of Robot Learning and HRI

• International Symposium on Experimental Robotics (ISER) 2025 is next week! Santa Fe, NM, USA, July 6 - 10, 2025
  
  

• Subscribe to the Robot Manipulation Events Google Calendar to stay in the loop!

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Adam Norton, Community Facilitator, COMPARE Ecosystem

Improving Open-Source and Benchmarking for Robot Manipulation

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