ObotX - Open Source Robotics

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ObotX - Open Source Robotics

ObotX - Open Source Robotics

@open_robotx

- open source robotics - total cost $3999 - globally patented #universalrobotics #robot #opensource #physicalai #embodiedai

California, United States Katılım Haziran 2024
234 Takip Edilen577 Takipçiler
ObotX - Open Source Robotics
@TheReapsZ In human environments - flat flors and stairs. Also when cooperates with second robot - two arms. It also climbs a stairs - it's no problem for tripod.
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ObotX - Open Source Robotics
Our blueprint for the "Optimal Universal Robot": ❌ Legs: Too complex, too expensive. ✅ Wheels: Fast, stable, 10x cheaper. ❌ Rotary Joints: Massive torque stress, custom gears. ✅ Of the shelf parts & linear actuators: High payload, extrem simplicity, off-the-shelf parts.
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Igor Strebz
Igor Strebz@xamgore·
@open_robotx – Can’t open boxes and take out items – Can’t see exactly what it grabs – Can’t sort through expired products – Can’t move a cart – Can’t put stuff on its head – Can’t clean the floor – Can’t stop a shoplifter – Can’t make R2D2 sound 😬😬😬
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Reza Sayar
Reza Sayar@iamRezaSayar·
@open_robotx this is so freaking awesome! 🔥🔥 do we have an ETA for the release date? 👀
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ObotX - Open Source Robotics
@MattTrainer For your personal/research purposes you can build it for free and do all what you want - just send us videos :). If you would like to sell, we take just 2% of sales :)
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Matt Trainer
Matt Trainer@MattTrainer·
@open_robotx Open source but globally patented? How does your license work? Would love to build this in my shop but patent wars suck.
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ObotX - Open Source Robotics
Progress on our universal mobile manipulator. We believe this is the optimal construction (cost-efficiency). How do you like it? :) Stay tuned for the next milestones.
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ObotX - Open Source Robotics@open_robotx·
Why are we still building monolithic robots? 🤖❌ In the 90s, we upgraded PCs part-by-part. We’re doing the same for robots. ✅ Exchangeable parts (hands, bases, sensors) ✅ Multiple simple robots cooperating on complex tasks ✅ Lower costs + easier maintenance
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ObotX - Open Source Robotics
ObotX - Open Source Robotics@open_robotx·
Universal mobile manipulators have a much greater chance of becoming the future of mass robotics than humanoid robots: 99% of the needed use cases are flat floors and stairs, where wheels are much more efficient (energy, speed, stability, cost, etc.). They also cost 10 x less
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Yawar Siddiqui
Yawar Siddiqui@yawarnihal·
Introducing ShapeR, a method for robust conditional 3D shape generation from casually captured sequences. ShapeR leverages a rectified flow transformer conditioned on per-object multimodal data to turn casual image sequences into full metric scene reconstructions. Project Page: facebookresearch.github.io/ShapeR Paper: arxiv.org/abs/2601.11514 Links to code and huggingface below ⬇️
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Davide Scaramuzza
Davide Scaramuzza@davsca1·
Check out our latest work, "Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning for Agile Flight," published in the IEEE Transactions on Robotics, where we reconcile #OptimalControl and #ReinforcementLearning, achieving the same super-human performance, but with superior generalizability, as our previous model-free deep RL! Code released! PDF: arxiv.org/pdf/2306.09852 Code: github.com/uzh-rpg/acmpc_… Full Video: youtube.com/watch?v=_qekrF… Model-free #ReinforcementLearning (RL) is known for its strong task performance and flexibility in optimizing general reward formulations. On the other hand, #ModelPredictiveControl (MPC) provides robustness, constraint handling, and powerful online replanning capabilities. In this work, we extend our previous AC-MPC paper (Romero, ICRA'24) by taking a deeper look at how both approaches can be unified. We introduce and extend Actor-Critic Model Predictive Control (AC-MPC), a framework that embeds a differentiable MPC inside an Actor-Critic RL architecture. This integration allows the MPC-based actor to perform short-term predictive optimization, while the critic facilitates long-horizon learning and exploration. We conduct a comprehensive study that highlights AC-MPC’s key advantages: - Better out-of-distribution generalization, both against unknown disturbances and changes in the quadrotor dynamics - Improved sample efficiency - A novel empirical analysis uncovering a relationship between the critic’s value function and the MPC cost function, providing deeper insight into their interplay. We validate our method in simulation and the real world on a quadcopter flying at superhuman speeds of up to 21 m/s, matching state-of-the-art model-free RL performance, and retaining the predictive structure of MPC for more reliable out-of-distribution behavior. Reference: Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning for Agile Flight IEEE Transactions on Robotics (T-RO), 2025 PDF: arxiv.org/pdf/2306.09852 Full Video: youtube.com/watch?v=_qekrF… Code: github.com/uzh-rpg/acmpc_… Kudos to @roaguiangel, @EliJalbout, @realyunlong! @UZH_en @UZH_Science @UZHspacehub @AUTOASSESS_EU @ERC_Research @UZH_ai
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Jason Shin
Jason Shin@jungwonshin95·
We are hiring senior ML engineer, robot learning. Come build robots that work reliably in the real world. We're pushing robot policies beyond demos into production! Apply below.
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ObotX - Open Source Robotics
ObotX - Open Source Robotics@open_robotx·
We are thrilled to announce the release of our latest open-source Mobile Manipulator Github repository. This release marks a significant milestone in our mission to make advanced robotics accessible to everyone. 🔗 Explore the repo in comments link. Please add star on Github
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Lukas Ziegler
Lukas Ziegler@lukas_m_ziegler·
This is not a mechanical frog! 🐸 It's a tripteron, a parallel-axis manipulator. Basically, a XYZ platform that moves in three directions using precision linear stages. The movement system is based on a kinematic design from Laval University, optimized for stability and efficiency with fewer moving parts. A key feature is the single long base axis, which simplifies the structure while allowing wide-range movement. The real beauty of mechanical engineering! 😮‍💨
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ObotX - Open Source Robotics
ObotX - Open Source Robotics@open_robotx·
Progress on our super simple universal manipulator, solving 99% humanoid use cases with 10x higher load capacity and 10x lower costs. Anyone interested in the source codes and construction repository? :) Please comment and follow to get updates. #robotics #humanoids
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ObotX - Open Source Robotics
ObotX - Open Source Robotics@open_robotx·
Mobile manipulator use case: arranging products on shelves in the store. Physically accurate simulation made in Google DeepMind MuJoCo. Full autonomy achieved with MPC strategy and PID operation.
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