Software

What are the Key Engineering Challenges in Autonomous Docking Systems and How are they Solved? (Part 2)

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Designing an ROS 2-based autonomous docking system is only half the story. Deploying it in the real world is another matter entirely. Since real industrial environments don’t cooperate with textbook assumptions, understanding these challenges will help […]

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How Robot Fleets achieve Full Mission Autonomy – From ROS 2 Autonomous Docking to Self-Charging (Part 1)

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. True operational autonomy requires more than mapping since robots have stringent expectations to meet. They must manage their own energy, return to charge when needed, and resume their missions without human intervention. e-con Systems has developed

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NVIDIA Expands NVIDIA Agent Toolkit With NVIDIA PhysicsNeMo and CUDA-X Libraries to Transform How the World Engineers, Designs and Builds

News Summary: NVIDIA expands NVIDIA Agent Toolkit with re-architected NVIDIA PhysicsNeMo libraries and updated NVIDIA CUDA-X libraries, enabling software developers to build autonomous AI engineers with AI physics skills, accelerated solvers and quantum chemistry capabilities. NVIDIA Nemotron 3 Ultra leads among open models in agentic register-transfer level coding with the ACE-RTL agent from NVIDIA Research,

NVIDIA Expands NVIDIA Agent Toolkit With NVIDIA PhysicsNeMo and CUDA-X Libraries to Transform How the World Engineers, Designs and Builds Read More +

Free Webinar on Automotive Perception in the Physical AI Era

On September 29, 2026 at 9 am PT (noon ET), Pierrick Boulay, Principal Analyst, Automotive Semiconductors, and Anas Chalak, Technology & Market Analyst, Imaging at Yole Group, will present the free hour webinar “Automotive Perception in the Physical AI Era: Imaging, Sensors and Computing,” organized by the Edge AI and Vision Alliance. Here’s the description,

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Avocado OS x Grinn: Rapid Physical AI Development on Edge Vision Hardware

At EVS 2026, Bill Brock, CEO of Peridio, joins Robert Atrea, CEO of Grinn Global, to announce a co-development partnership bringing Avocado OS to Grinn’s AstroSOM 1680 platform. Together, they demonstrate how Avocado OS integrates with Grin’s edge vision hardware to accelerate development of production-ready computer vision and physical AI applications. The demo highlights a

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Avocado Connect: From Dev Kit to Production for Physical AI Fleets (with Advantech)

In this video, Justin Schneck, CTO and Co-Founder of Peridio, introduces Avocado Connect, the fleet management platform for deploying and operating Avocado OS in production physical AI environments. He explains the gap between building on dev kits like NVIDIA Jetson and running reliable, scalable systems in the field—and how Avocado Connect is designed to bridge

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Device Infrastructure for Physical AI: Introducing Avocado OS

Justin Schneck, CTO and Co-Founder of Peridio, introduces Avocado OS, the company’s modern embedded Linux operating system designed for teams building physical AI devices and products. In this video, Schneck explains how the rise of physical AI has created one of the deepest and most complex software stacks engineering teams have faced—combining embedded Linux, AI

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How Robotic Color Sorting Works: Vision, Classification, and Motion Control from Camera to Gripper.

This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software.   Sorting apples by color sounds simple enough. In fact, it is the kind of project that often produces an impressive demo in a matter of hours. Put a camera above a conveyor, detect red apples,

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Nota AI Demonstration of LLM Acceleration on Mobilint NPU, Optimized with NetsPresso

Thibault Castells, Research Engineer at Nota AI, demonstrates the company’s latest edge AI technologies at the 2026 Embedded Vision Summit. Specifically, he demonstrates Qwen3-4B running as a real-time LLM Coding Assistant entirely on Mobilint MLA100 NPU, optimized with NetsPresso. Achieving 179–478ms Time to First Token and 8.5–10.8 tokens per second, the demo proves that high-performance

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Nota AI Demonstration of VLA Robotics on Dragonwing, Enhanced by NetsPresso

Thibault Castells, Research Engineer at Nota AI, demonstrates the company’s latest edge AI and vision technologies at the 2026 Embedded Vision Summit. Specifically, he demonstrates VLA optimization on Qualcomm Dragonwing IQ-9075, powered by NetsPresso. Using an Action Head-only optimization approach, Nota AI achieves 7x faster Action Head speed (218ms → 31ms) and 1.6x faster end-to-end

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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