Fernando Cladera

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! youtube.com/watch?v=sSEBcn…

This is really impressive, in line with everything that @tom_jiahao makes!

Outstanding presentation @ZiyunClaudeWang !!

Wanna see how we recorded the 2024 total solar eclipse using event cameras? I will present 🌑 "Looking into the Shadow" at the #CVPR2025 Workshop on Event-based Vision! Website: eclipse-event.cam @smartereveryday @KostasPenn @KenIsNotARobot @vijay_r_kumar @guillermogb

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

I will present my work on high-altitude orthomapping with event cameras in a few minutes. Join me in room 305A! evmapper.fcladera.com

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

Hello Atlanta! I am excited to be at #ICRA2025, meet old and new colleagues, and present some of our recent work. Are you around? Get in touch!

You have until June 2 to send your submissions on Codabench! #CVPR2025 @KenIsNotARobot @ZiyunClaudeWang @AnthonyBisulco @ChrisKorpela @KostasPenn @vijay_r_kumar @guillermogb @PennEngineers @GRASPlab

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 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. m3ed.io/slam_challenge/

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!

This workshop will bridge industry and academia to discuss how to close the gap towards autonomous robots in agricultural and field robotics settings.

Dear friends and colleagues, we are excited to invite you to our workshop "Novel Approaches for Precision Agriculture and Forestry with Autonomous Robots" ag-tech-icra2025.com 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. kicad.org/blog/2025/02/V…

Excited to have all the Dronecode folks in Philly! It is going to be a lot of fun!! linkedin.com/posts/px4_exci…

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. buff.ly/4cqZ94o 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.

@mrpollo Volar drones ilegal 🎶

Correr es mi destino por no llevar papel🎶