One robot is cleaning the kitchen. Another needs to get in there to cook dinner. Both are doing what you asked, but now one has to wait. Who decides?

I don’t want to be settling arguments between appliances 😄 If I have to constantly coordinate them, I’ve just given myself a new job.

I’d rather have one home “brain” that knows my priorities and manages the devices accordingly. I tell it we’re usually home by 6 and want dinner ready. It figures out when to clean, when to cook, and what needs to change if something runs late.

That brain wouldn’t need a body, and it could coordinate other home systems too. But I’d decide how much freedom it gets, when it needs to ask me, and which systems stay separate. Maybe I want my alarm system or cameras completely outside its control.

Personally, I’d want it running locally, with remote access when I’m away. And it should work with different brands. Buying one robot shouldn’t lock me into that manufacturer for everything else.

How would you handle this: one home brain coordinating everything, or robots negotiating with each other? And when they can’t agree, does the problem just come back to us?

Look at my robot spider. I can programme and let him to do whatever I want. Kick the ball, push the obstacles, wave to me . I can explore more.

Currently working on my final year project on building open source framework to manage the full stack development of agent swarms. I want to build this to support robotics developers and enthusiasts to specifically build heterogeneous and homogeneous antigenic swarms.

I don't want this to remain a thesis or simply a good theory of what should be done, but have it actually be utilized by robotics developers. I'm very interesting in making this as useful for the community by catering to any problem across the robotics stack, from simulation to telemetry.

What does your development stack look like, and what are your pain points? Would love to know.

Reach me: https://www.linkedin.com/in/anzonathan/

The lab containers had working latches. The factory’s containers had been battered through repeated use, and the tables used to rotate them were rusted. Both changed how the robot needed to handle the task.

Jagdeep Singh, CEO of Rhoda AI, describes how the team adapted the robot using roughly three hours of additional data collected in the factory, after initially thinking it had mastered the process.

Full episode: https://www.youtube.com/watch?v=Mx1SaWRQbE0

Put Quaddle on a patch of gravel and just wanted to see it walk. Its IMU (gyroscope + accelerometer) was trying to correct for the uneven ground in real time, but it just started wobbling — loose gravel is apparently brutal for a quadruped's balance.

What other terrains should Quaddle try?

This is TAKTO ONE, a tendon-driven hand exoskeleton I built for my master’s thesis. Each of the 12 finger joints has its own magnetic encoder, and the twin in the headset moves from those sensors and two IMUs, not from camera tracking, so a hidden finger still gets measured.

It’s all open source (CAD, PCBs, firmware, build guide), and you can play with the twin in your browser, no hardware needed:
https://takto.one
https://github.com/molanocortes/takto-one

I defend the thesis tomorrow, so questions are very welcome :)

Galbot’s PASSAGE system helps humanoid robots adapt their whole-body movements to cluttered spaces by ducking, stepping over obstacles, or turning sideways. Tested on a Unitree G1, it completed 50 physical trials across 45 obstacle layouts without falling or requiring safety intervention. However, its simulated success rate dropped from 98.67% to 70.3% when avoiding all contact became mandatory, showing how difficult precise whole-body navigation remains.