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robotics

13 concise briefings covering robotics.

IEEE Spectrum 01 Oct 2026

IEEE Names 2027 Technical Field Award Recipients

IEEE announced its 2027 Technical Field Award recipients across disciplines including AI, microelectronics, medical robotics, wireless networks, and power electronics. The list highlights individual and team achievements cited for technical innovation, leadership, and societal impact, and nominations for 2028 open until 15 January 2028.

IEEE Spectrum 25 Sep 2026

Portable RoboMeshA brings robotics and AI lab to Guadalajara schools

A multidisciplinary team at ITESO in Guadalajara built RoboMeshA, a portable, self-contained robotics and AI learning platform that students access via a web browser without installing software. The team validated two units in local high schools and is developing modular coupling so multiple units can operate together (IEEE Spectrum).

IEEE Spectrum 17 Sep 2026

Rethinking Robot Safety: Cybersecurity Risks for Physical AI

IEEE Spectrum reports that modern robots combining multimodal sensors and AI are vulnerable to attacks that manipulate perception, models, or system components without obvious failures. The article outlines layered risks—poisoned training data, system and middleware exploits, and runtime input attacks—and recommends lifecycle-focused cybersecurity testing and monitoring (VicOne examples cited).

Google DeepMind Blog 13 Jul 2026

Google and AIM launch ATL Saathi to support Indian educators

Google DeepMind and India’s Atal Innovation Mission introduced ATL Saathi, an AI assistant powered by Gemini to help teachers run robotics labs. The tool is designed to guide educators with curriculum-aligned support and hands-on project help in school innovation spaces.

IEEE Spectrum 13 Jul 2026

X Square Robot proposes integrated foundation stack for general-purpose robots

X Square Robot outlines an open embodied-AI stack combining curated interaction data, an event-oriented world model (WALL-WM), and a pretrained action model (Wall-OSS-0.5) with a semantic action tokenizer. The company emphasizes data validity through physical replay and claims cross-embodiment transfer and deployable pretraining before fine-tuning, while noting most results come from its own robots and benchmarks.

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