r/robotics

We need some tank sim players for pre-pre-alpha testing in the next few weeks.

The video shows our real robots and virtual gameplay. We're getting ready to launch virtual battles on dedicated servers against other players so you can get in on the action!

The virtual battle client is designed to reflect the real robots as closely as possible.

Hey r/robotics,

Like many in the open-source community, we’ve been frustrated by the massive hardware premiums required to get into embodied AI research. Industrial AMRs and collaborative setups easily cross the $50k mark.

We wanted to change that, so we co-developed Mobile OpenArm X1 alongside OpenArm. It is a fully transparent, modular development platform engineered specifically for low-level control, simulation, and data collection.

We managed to scale the hardware cost down significantly. For context, the base Education Edition features a LiDAR-guided autonomous mobile robot paired with a 16-DoF arm/gripper setup, hitting a hardware cost of $9,000.

Core Specs & Tech Stack:

• Mobility & Kinematics: 4WD omnidirectional AMR base supporting 360° spatial turning and continuous 360° waist rotation.
• Sensing: Integrated LiDAR tracking and odometry for global localization, centimeter-level positioning, and dynamic obstacle avoidance.
• AI / Model Training: Native spatial-action data fusion (LiDAR point clouds + joint states) optimized for training Vision-Language-Action (VLA) models.
• Software Ecosystem: Out-of-the-box support for Hugging Face LeRobot, ACT, and Diffusion Policy, alongside simulation integration for Isaac Gym and MuJoCo.
• Transparency: Complete access to low-level driver source code and unified APIs.

Our goal is to build an open foundation so developers can iterate faster without proprietary walls. The platform is currently up for pre-order, and the entire stack is decoupled and modular.

We'd love to hear your thoughts on the hardware layout. Are there specific sensor payload configurations or simulation environments you’d like to see natively supported out of the box?

• Full disclosure: I am part of the core team building NVatom.

Mobile OpenArm

Hey everyone, looking for a sanity check on a heavy-payload AMR project (~700kg payload) running on a 48V LiFePO4 pack.

Whenever the robot hits rough terrain or accelerates suddenly, the transient current draw causes our battery bus to sag hard, dipping down to 35V-36V for a few hundred milliseconds. Our current "industrial-grade" servo drives are losing their minds under this sag. We are hitting under-voltage faults that trigger random emergency stops, massive thermal spikes inside our sealed IP65 wheel hubs as the drives draw more current to compensate, and mushy velocity control right when we need tight torque response.

We’ve debated adding a bulky buck-boost regulator just to keep the drive logic stable, but it kills our payload-to-weight ratio.

For those building battery-powered platforms that survive high-torque transients, are you over-specifying the battery pack to stop the sag, or switching to drives with ultra-wide input voltage ranges? Also, how do you handle the thermal overhead in a sealed housing? Do GaN-based or ultra-high-efficiency drives actually solve the heat issue at the source?

Trying to avoid a massive chassis redesign just to fit a bulkier cooling system. Any advice?

For those of you running BLDC motors — what controller are you using and what frustrates you most about it?

I’m trying to build something and want to understand your needs.

What is the unreliable part of it?

I wanted to test how good is the new Gemma 4 model for practical edge applications (including tool usage, image labelling and audio transcription)

I tested the tool usage through the ROS-MCP server. The LLM was able to publish to ROS topics to complete the intended goal.

I also made it transcribe a 6 minute audio file from one of my old videos and it performed amazingly in that as well.

What's more surprising is that it's just a 2.3 billion effective reasoning model, runs locally on a 8GB device and provides impressive 15-17 tokens/sec.

Would love to know your thoughts on this? Has anyone here tried using gemma 4 on their jetson Nano? If yes, what did you do and how was your experience?

Hello, I'm working on several different ground robot designs, and I've sort of gotten stuck on the issue of suspension. Specifically, how does one determine how strong a suspension system needs to be for a given application? How do you model the forces acting on the drivetrain that need to be counteracted by the suspension? I've researched many types of suspension systems for various types of drivetrains, but while they make sense conceptually, I'm still trying to figure out the numbers to use to reduce it to a standard solid mechanics problem. Thank you for your assistance and any resources.

Automation discussions often make it sound like robotics adoption is happening everywhere equally.

But it still feels heavily industry-dependent. Automotive seems relatively mature.

Meanwhile, several mid-scale manufacturing environments still appear hesitant because integration and ROI timelines remain unclear.

Curious whether cost is still the primary concern or if implementation complexity is the bigger issue now.