A trajectory plot of a projectile alongside equations of motion on a chalkboard.

Physics Zero to Hero: A Self-Teaching Roadmap for Working Engineers

A working engineer’s guide to teaching yourself physics from the ground up, anchored in real systems like ROS, SPICE, and game engines.

September 4, 2026 · 11 min · 2135 words · martinuke0
A autonomous ride-hail vehicle navigating an urban street at dusk, with sensor housings visible on the roof.

How Cybercabs Work: The Engineering Behind Autonomous Ride-Hail

Cybercabs are not magic. They are a tightly integrated stack of perception, prediction, planning, and fleet operations software wrapped around an electric vehicle. This post walks through each layer with the production systems that ship it today.

September 4, 2026 · 11 min · 2178 words · martinuke0

Benchmarking Interaction, Beyond Policy: Summarizing QAsk-Nav for Everyone

Introduction Imagine you’re in a large, unfamiliar warehouse and you need to find a specific red toolbox. You can see the aisles, but you can’t see the entire building at once. To succeed, you might ask a coworker, “Is the toolbox near the loading dock?” The coworker’s answer helps you narrow down where to look. In the world of artificial intelligence, giving a robot the ability to navigate a space and ask clarifying questions to a human partner is a huge step toward truly collaborative machines. ...

April 2, 2026 · 8 min · 1630 words · martinuke0

Optimizing Low Latency Edge Inference for Distributed Autonomous Robotic Swarms Beyond Cloud Connectivity

Introduction The promise of autonomous robotic swarms—hundreds or thousands of lightweight agents cooperating to achieve a common goal—has moved from science‑fiction to real‑world deployments in agriculture, logistics, surveillance, and disaster response. A critical enabler of these deployments is edge inference: running machine‑learning (ML) models directly on the robot’s on‑board compute resources rather than streaming raw sensor data to a remote cloud for processing. Why does latency matter? In a swarm, each agent’s decision influences the collective behavior. A delay of even a few hundred milliseconds can cause collisions, missed deadlines, or sub‑optimal coordination. Moreover, many operating environments (underground mines, remote farms, battlefield zones) suffer from intermittent or non‑existent broadband connectivity, making reliance on a central cloud infeasible. ...

April 1, 2026 · 11 min · 2287 words · martinuke0

Deep Dive into the Microsoft CCR Session API

Table of Contents Introduction Why the Concurrency and Coordination Runtime (CCR) Exists Core Building Blocks of CCR 3.1 Dispatcher 3.2 Port & Receiver 3.3 Task, Arbiter, and Interleave The Session API – Overview 4.1 Session Lifetime 4.2 Creating a Session 4.3 Adding Work to a Session 4.4 Cancellation & Cleanup Practical Example 1 – Coordinating Multiple Web Service Calls Practical Example 2 – Sensor Fusion in a Robotics Scenario Advanced Topics 7.1 Nested Sessions 7.2 Session Pooling & Reuse 7.3 Interoperability with async/await 7.4 Debugging Sessions Performance Considerations & Common Pitfalls CCR Session API vs. Other Concurrency Models Conclusion Resources Introduction When you build modern, responsive applications—especially in domains like robotics, IoT, or high‑throughput services—handling asynchronous work efficiently becomes a core architectural challenge. Microsoft’s Concurrency and Coordination Runtime (CCR), originally shipped with Microsoft Robotics Developer Studio (MRDS), offers a lightweight, message‑driven model for orchestrating asynchronous operations without the overhead of heavyweight threads. ...

March 31, 2026 · 14 min · 2966 words · martinuke0
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