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Products that do what FusionCore: ROS 2 sensor fusion that outperforms robot_localization does
I built sensor fusion for a mobile robot and reached for robot_localization like everyone does. After spending too long fighting navsat_transform, UTM zone boundaries, and YAML covariance tuning, I wrote my own. FusionCore is a 22 state UKF that fuses IMU, wheel encoders, and GPS in ECEF directly (no coordinate projection, no extra node). It estimates IMU bias, adapts its noise covariance automatically from the innovation sequence, and gates outliers with a chi squared test on every sensor. I benchmarked it against robot_localization EKF on 6 sequences from the NCLT public dataset…
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Hi all, excited to share our latest work, OK-Robot, which is an open and modular framework to perform navigation and manipulation with a robot assistant in practically any homes without having to teach the robot anything new! You can simply unbox the target robot, install OK-Robot, give it a "scan" (think a 60 second iPhone video), and start asking the robot to move arbitrary things from A to B. We already tested it out in 10 home environments in New York city, and one environment each in Pittsburgh and Fremont. We based everything off of the current best machine learning models, and so…
2024 · ok-robot.github.io
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I built LocalGPT over 4 nights as a Rust reimagining of the OpenClaw assistant pattern (markdown-based persistent memory, autonomous heartbeat tasks, skills system). It compiles to a single ~27MB binary — no Node.js, Docker, or Python required. Key features: - Persistent memory via markdown files (MEMORY, HEARTBEAT, SOUL markdown files) — compatible with OpenClaw's format - Full-text search (SQLite FTS5) + semantic search (local embeddings, no API key needed) - Autonomous heartbeat runner that checks tasks on a configurable interval - CLI + web interface + desktop GUI - Multi-provider:…
Feb 2026 · github.com
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This little project came about because I kept running into the same problem: cleanly differentiating sensor data before doing analysis. There are a ton of ways to solve this problem, I've always personally been a fan of using kalman filters for the job as its easy to get the double whammy of resampling/upsampling to a fixed consistent rate and also smoothing/outlier rejection. I wrote a little numpy only bayesian filtering/smoothing library recently (https://github.com/hugohadfield/bayesfilter/) so this felt like a fun and very useful first thing to…
2024 · github.com
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Sup HN, So I got tired of bouncing between Flightradar, MarineTraffic, and Twitter every time something kicked off globally, so I wrote a dashboard to aggregate it all locally. It’s called Shadowbroker. I’ll admit I leaned way too hard into the "movie hacker" aesthetic for the UI, but the actual pipeline underneath is real. It pulls commercial/military ADS-B, the AIS WebSocket stream (about 25,000+ ships), N2YO satellite telemetry, and GDELT conflict data into a single MapLibre instance. Getting this to run without melting my browser was the hardest part. I'm running this on a laptop…
Mar 2026 · github.com
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Sowbot is an open-hardware agricultural robot designed to close the "prototype gap" that kills most agri-robotics startups and research projects — the 18+ months spent on drivers, networking, safety watchdogs, and UI before you can even start on the thing you actually care about. The hardware is built around a stackable 10×10cm compute module with two ARM Cortex-A55 SBCs — one for ROS 2 navigation/EKF localisation, one dedicated to vision/YOLO inference — connected via a single ethernet cable. Centimetre-level positioning via dual RTK GNSS, CAN bus for field comms, and real-time…
Feb 2026 · sowbot.co.uk
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Hey Folks! I've been building an open source benchmark for measuring local LLM performance on your own hardware. The benchmarking tool is a CLI written on top of Llamafile to allow for portability across different hardware setups and operating systems. The website is a database of results from the benchmark, allowing you to explore the performance of different models and hardware configurations. Please give it a try! Any feedback and contribution is much appreciated. I'd love for this to serve as a helpful resource for the local AI community. For more check out: - Website:…
2025 · localscore.ai
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Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024
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Trace LLM requests + costs with OpenTelemetry monitoring
Oct 2025
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Vision models have been gaining popularity as a replacement for traditional OCR. Especially with Gemini 2.0 becoming cost competitive with the cloud platforms. We've been continuously evaluating different models since we released the Zerox package last year (https://github.com/getomni-ai/zerox). And we wanted to put some numbers behind it. So we’re open sourcing our internal OCR benchmark + evaluation datasets. Full writeup + data explorer here: https://getomni.ai/ocr-benchmark Github: https://github.com/getomni-ai/benchmark Huggingface:…
2025 · getomni.ai
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Every once in a while, I hear developers complain about how working with ROS2 frustrates them, or students who find the barriers to understanding ROS2 too high. Undoubtedly, ROS2 was originally designed in the lab for the prototyping phase. However, being widely adopted has turned its design into a messy blob that is not only "thick" - and not in a good way - but also too tangled. Therefore, I came up with the design for HORUS -Hybrid Optimized Robotics Unified System. At first, I was just experimenting to see whether building a system that respects both the versions and dependencies of…
Nov 2025 · github.com
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Hey HN, Nir, Gal and Tomer here. We’re open-sourcing a set of extensions we’ve built on top of OpenTelemetry that provide visibility into LLM applications - whether it be prompts, vector DBs and more. Here’s the repo: https://github.com/traceloop/openllmetry. There’s already a decent number of tools for LLM observability, some open-source and some not. But what we found was missing for all of them is that they were closed-protocol by design, vendor-locking you to use their observability platform or their proprietary framework for running your LLMs. It’s still early in the…
2023 · github.com
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2021 · floptimal.com
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Hi HN, I’m building Waycore, an open-source project exploring what a flexible, offline-first field computer should look like for outdoor, survival, and off-grid scenarios. The core goals are adaptability and resilience: modular hardware (external sensor/tool modules) extensible OS with support for external apps (guidelines in progress) no required internet connection — maps, models, and knowledge work offline optional LTE/Wi-Fi when available and explicitly enabled A major focus is on-device agentic AI, not just chat or image recognition. The AI is intended to: read live sensor…
Dec 2025
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Jun 2026 · github.com
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I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com
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High performance storage engine for efficient LLM inference and GPU Training.
18h ago · theopenlake.com
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Combining (1) open-source autopilots with (2) open-source ROS2 simulation/navigation/mapping packages and (3) open-source, hardware-accelerated computer vision should not be hard, but it is. aerial-autonomy-stack aims to solve this by collapsing (1) multi-robot, (2) software-in-the-loop, (3) hardware-in-the-loop simulation, (4) CI/CD, and (5) deployment into a single containerized workflow. The end-to-end stack can be re-created/simulated with a one-liner (45') build on Ubuntu >=22.
Jun 2026 · github.com
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We built HALO (Hierarchal Agent Loop Optimizer), an open-source tool for debugging and optimizing AI agents using their execution traces. It’s a loop. Run your agent, feed the traces to HALO, get the report, apply the fixes, then re-run your agent. HALO takes in OTEL compliant traces from AI agents using tracing frameworks such as Langfuse, Arize/OpenInference, or even just plain JSONL. It uses an RLM (Recursive Language Model) to more efficiently break trace analysis into smaller subproblems in order to find recurring patterns across large amounts of data and fix systemic issues that…
Jun 2026 · github.com
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Hey everyone, I wanted to share what I have been working on recently. I had this itch for a long time to figure out if terrain contour matching could help with ground navigation, by only only relying on iphone's sensors and public data. So far I have had decent results. This is a working prototype, but there is a lot that is in the pipeline. If you notice anything weird, let me know or open a PR. Any feedback, comments are welcome :)
Jun 2026 · github.com
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