Introducing Muscle v0 -- infinite degrees of freedom, from @DaxoRobotics. A different mountain to climb - with a far more beautiful peak.
We built this from the ground up:
- Ultra-dexterous
- Built for machine learning
- Durable and robust
More below (1/n)
The PX4 meetup presentation recording is out! Thanks @MikePehel, @mrpollo and @Dronecode for this amazing opportunity to meet other folks working on open source robotics. I hope we can do it again soon!
https://t.co/XEAUVxL0lv
We at @DaxoRobotics found a new (and better) way to build towards true robot dexterity.
This dexterous robotic hand is something I’ve been working on since graduating from @GRASPlab.
Below is just a teaser. Enjoy the spin. The full story drops tomorrow.
Congratulations Prof.Dr. Wang @ZiyunClaudeWang for the exceptional defense presentation! @JohnsHopkins ECE is so fortunate to win you! Thank you Pratik, Lingjie, CH and Davide!
I'm excited to share that I will join Johns Hopkins ECE (@JHUECE, @HopkinsEngineer, @HopkinsDSAI ) as an Assistant Professor in Fall 2025. My lab will focus on embodied AI, emphasizing efficient, adaptive, and robust robotic systems using neuromorphic technologies.
I will present our work on air-ground collaboration with SPOMP in 407A in a few minutes! We deployed 1 UAV and 3 UGVs in a fully autonomous mapping mission in large-scale environments. Come check it out! #ICRA2025@GRASPlab@pxlweavr
We (authors and editors) worked very hard to finalize Part III of the SLAM Handbook before #ICRA2025. It is available for public comment, link below. Please keep flagging issues coming as we work towards finalizing the draft for the Cambridge UP print version. #SLAMHandbook
We are releasing the M3ED SLAM Challenge for the CVPR 2025 Workshop on Event-based Vision! 🚀 The goal of this challenge is to leverage the high temporal and spatial resolution of HD event cameras for SLAM and pose estimation applications.
https://t.co/yysR9UR4r5
We are hosting two tracks:
- Event (+ IMU): if you obtain your pose using a single or a pair of event cameras, w/wo IMU.
- Event + Mono (+ IMU): if you obtain your pose using a single or a pair of event cameras fused with monocular global shutter cameras, w/wo IMU.
We have an exciting line of confirmed speakers on our website. The Call for Papers is also available, with a deadline of April 15. We will release a tree diameter estimation challenge soon as part of the workshop. Stay tuned!
Dear friends and colleagues, we are excited to invite you to our workshop "Novel Approaches for Precision Agriculture and Forestry with Autonomous Robots" https://t.co/8fdOCKptdu at ICRA 2025!
KiCad Version 9.0.0 Release
The KiCad project is proud to announce the latest major version stable release. See the blog post on the KiCad website for more information about this release.
https://t.co/LX9suroyJE
Data collection for forestry, timber, and agriculture currently relies on manual techniques which are labor-intensive and time-consuming.
TreeScope is the first semantically segmented lidar dataset collected with robotic systems in agricultural environments. It provides lidar data and ground-truth data for semantic segmentation and diameter estimation from agricultural environments to address the counting and mapping of trees in forestry and orchards.
This example visualizes data from their custom sensor platform, including sensor data from lidar, IMU, GPS, RGBD and thermal cameras, along with ground-truth data with over 1,800 manually annotated semantic labels for the tree stems and field measurements of tree diameters.
Check out their Github repo for an overview on how to use the data and benchmark scripts to evaluate the performance of diameter estimation and semantic segmentation algorithms, along with their website for more info.
https://t.co/J3AGCvxzAb
The Treescope dataset has been provided by the research of Vijay Kumar, Dean of Penn Engineering and Kumar Robotics, Derek Cheng, Fernando Cladera, Ankit Prabhu, Xu Liu, Alan Zhu, Patrick Corey Green, Reza Ehsani, and Pratik Chaudhari.