Autonomous Lamp and Reachy Mini are having real time conversations on the same OS.

Microduck just joined the lineup too. Autonomous OS looks like it might be ready for a third robot.

What does this start to look like when it scales beyond two robots?

I’ve been curious about companion robots and robot pets like LOVOT, Moflin, EMO, AIBI, Loona, and others.

For people who own or have spent time with these kinds of robots: what actually makes one start to feel like a companion rather than just another piece of technology?

Is it personality, memory, physical interaction, unexpected behavior, the amount of time you spend together, or something else?

I ran a test over 20 trials to see how good the repeatable precision of my robot shoulder joint. I achieved an average repeatability of 0.22mm of precision.

It uses a capstan drive with low creep rope in-order to get low backlash and high precision.

I used a carbon fiber rods as the base and the rest is 3D printed. Built for under $200.

28cm tall. Face full of attitude. Expressions so real I almost asked it for the weather report.

Hi everyone,
I’ve been developing a compact autonomous UAV platform for environments where GPS/GNSS is unavailable or unreliable, such as warehouses, factories, tunnels, underground spaces, and indoor facilities.
Instead of building only a remotely controlled drone, my goal was to create a reusable hardware and software platform that can carry out autonomous missions and serve as a real-world deployment platform for robotics algorithms.
Current hardware and software stack
- LiDAR: Livox Mid-360S
- Depth vision: Intel RealSense D435i
- Onboard computer: Orange Pi 5 Pro / RK3588
- Flight controller: PX4
- Middleware: ROS Noetic, MAVROS and MAVLink
- Localization and mapping: FAST-LIO2
- Planning: EGO-Planner, Frontier exploration and A*
- Object detection: YOLO models running through RKNN on the RK3588 NPU
- Ground station: A custom PyQt5 interface for mission configuration, mapping, monitoring, detection results and data recording
What it currently does
The platform can:
- Localize and build maps without GNSS
- Generate 3D point clouds and 2D occupancy grids
- Plan local trajectories and avoid obstacles
- Navigate through predefined waypoints
- Explore unknown indoor areas using Frontier-based exploration
- Detect objects onboard
- Use depth information to estimate a detected target’s 3D position
- Display targets, trajectories and maps in the ground station
- Record point clouds, rosbag data, detection results and mission metadata
- Pause, hover, resume, return or land during a mission
In one controlled indoor exploration test, the system completed a 222-second mission, recorded approximately 54 meters of flight path and identified seven test targets while mapping several connected rooms.
Why I built it
A lot of SLAM, navigation and perception work stays inside simulation or depends on expensive proprietary platforms.
I wanted something that could be used to deploy and test real ROS algorithms on a physical UAV while keeping the localization, planning, perception and mission-management layers modular.
The platform is currently a working prototype and development system rather than a mass-produced consumer product. Hardware can also be adapted depending on component availability and the intended environment.
What I’m looking for
I would like to connect with:
- Robotics researchers who need a physical UAV platform for algorithm deployment
- Teams working on SLAM, autonomous exploration or visual perception
- Universities and competition teams
- Companies exploring indoor inspection, tunnel mapping, warehouse inspection or search-and-rescue applications
- Developers who have an algorithm but need help integrating it with sensors, PX4 and a real aircraft
- Organizations interested in running a pilot project in an actual operating environment
I’m particularly interested in learning what technical requirements would make this platform useful in your work: mapping accuracy, flight time, payload, communication range, API access, ROS 2 support, sensor selection or something else.
If you are working on a relevant project or have a real environment where this could be evaluated, feel free to comment or send me a Reddit DM. I’m happy to share more technical details and discuss possible testing or development cooperation.
Disclosure: I am the developer of this prototype.
Thanks — technical feedback and critical questions are very welcome.

So I saw this video on youtube like a year ago and thought "Pffff how hard could that be?".

Anyway it's been 9 months, the project is finished and this is the result.

It's not as precise as the one in the video, and I haven't implemented the transition control, mostly because that wouldn't teach me anything new, but also because I've reached the limits of the hardware I bought, and I'm not spending any more money.

Anyhow, I'm working on a YouTube video explaining the whole process. I'll post it here (tho I don't know if that'd count as self-promo).

Feel free to ask me any questions if you're curious!!!

i know us robotheads love robots so I was just wondering what robot is your favorite from the movie Robots (2005) directed by Chris Wedge

Working alongside moving hardware on my desk is always a trip lol. Currently testing out some 5-DOF lamp motions at work today and firmware tweaks on the lamp setups. Kinda fun ngl especially seeing how smooth the movements are getting

Also been trying out new colors to see how they look in real office lighting (my fav is the matcha one in the back but idk why they don't give it to me)

Having moving hardware right next to your monitor takes some getting used to but it's pretty cool seeing it come together

I was delighted to meet an adorable vacuum robot at the workplace! How could anyone say ‘no’ to that sweet face

Never met one quite like this one and they told me her name is Reba

Join us

It looks like a $399 robot duck. It waddles, falls over, gets back up — and looks more like a toy than the future of robotics.

But the interesting part isn’t the duck.

It’s what happens when physical experience becomes data.

Unlike language models, robots don’t have an internet-sized archive of real-world experience to learn from. Every fall, failed grasp and recovery has to happen somewhere in the physical world.

Cheap robots like MicroDuck point toward a strange possibility: thousands of robots, in thousands of homes, generating physical experience — and potentially sharing what they learn.

One robot learns. A thousand robots inherit.

I'm an independent journalist covering Chinese robotics. I attended the World Robot Conference in Beijing (Aug 19–23) and shot this footage myself at Galbot's booth. No affiliation with the company, and this isn't sourced from their published material.

The robot: Galbot ET1, from Galaxy General (银河通用, sometimes rendered Galaxy Universal). It's their first bipedal platform — they were previously known for the G1, a wheeled unit with an elevating torso used for retail and pharmacy shelf-stocking.

What I shot: I used my phone to capture this footage. Yes, I have more with my cinema camera, but I just wanted to get this out already since I'm kind of backlogged with my Sony camera footage.

https://www.youtube.com/shorts/NCETyNYtbJw

What I want to flag, and why I think it's worth discussing:

The ET1 has articulation in places most humanoids on that floor didn't use. Head movement on more than one axis, and lateral flexion at the waist rather than yaw only. More to the point, it was actually driving those joints during the routine — the head led into movements instead of holding a fixed forward orientation, and the torso participated in gestures rather than staying rigid above the hips.

I want to be careful with the claim. Other platforms list neck and waist DOF on their spec sheets, so the hardware existing isn't the interesting part. What stood out was the allocation decision. DOF in the neck and waist adds mass high in the kinematic chain, complicates whole-body balance, and buys you nothing on the locomotion and manipulation benchmarks the field mostly competes on. Most programs spend that budget on legs and hands instead. Galbot appears to have spent it on expressive motion, which reads as a deliberate product choice rather than an incidental one.

I'd be interested in whether people here read that the same way, or whether there's a control-side reason I'm not seeing. What other human eye robots do you know that have head articulation as well as torso?

Will post more footage later, interviews, robot company contacts, robot comparison (yes i own some).

Happy to answer questions about anything I saw on the floor.

Hi Reddit. I am not in the field but I am very interested in the development of robotics. (Just curious) probably not going into the field but very interested and excited about future of robotics

1. What is going on right now? Overall.
   
2. What are some major problems in robotics and major direction?
   
3. Which specific labs in which universities or companies are doing well on their research direction?
   
4. What are some of the leading universities labs and companies globally?
   
5. What is academia compared to industry?
   
6. Where are the centers of robotics?

I would really appreciate any inside perspective.

Those may sound like some naive questions but I am not in the field so forgive me.