Tagged articles

robot control

5 articles · Page 1 of 1

Sep 30, 2026 · Artificial Intelligence

RoboICL: Frozen GPT-6 Astra Achieves SOTA Robot Control via In-Context Learning

RoboICL enables frozen GPT-6 Astra to control dual-arm robots by providing demonstrations and the robot's own execution history as embodied context, achieving 50.64 average progress score on 30 RoboDojo tasks—surpassing prior methods—with detailed analysis of memory design, real-robot transfer, and 929 executable trajectories for inspection.

Embodied AIGPT-6 AstraRoboDojo

0 likes · 19 min read

RoboICL: Frozen GPT-6 Astra Achieves SOTA Robot Control via In-Context Learning

Machine Heart

Sep 26, 2026 · Artificial Intelligence

Show-Harness: A Semantic Action Interface Lets VLMs Control Real Robots Zero-Shot

Show-Harness introduces an Embodied Harness — a semantic action interface enabling vision-language models to control diverse robots through interpretable, composable actions like move, rotate, grasp, and release, achieving 89–100% zero-shot success across tasks, environments, and embodiments while unifying human teleoperation, GUI agents, and VLM control via the GUMI interface.

Embodied AIGUMISemantic Action Interface

0 likes · 16 min read

Show-Harness: A Semantic Action Interface Lets VLMs Control Real Robots Zero-Shot

Machine Heart

Jun 29, 2026 · Artificial Intelligence

Control Humanoid Robot Motion with a Sentence or Music via OMG Framework

OMG introduces a hierarchical “generation brain + tracking cerebellum” framework that leverages a large multimodal dataset and diffusion‑based OMG‑DiT network to let humanoid robots synthesize full‑body motions from a single sentence, music clip, or pose, achieving state‑of‑the‑art performance across text, audio, and motion benchmarks.

AI generationOMG frameworkdiffusion models

0 likes · 11 min read

Control Humanoid Robot Motion with a Sentence or Music via OMG Framework

AntTech

May 26, 2026 · Artificial Intelligence

Enabling Robots to “Think While Acting”: LingBot-VA Paper Accepted at RSS 2026

Researchers from AntLingbo and Hong Kong University present LingBot-VA, a causal world modeling framework for robot control that predicts future environment changes and generates actions, achieving up to 98.5% success on benchmarks and over 20‑point gains with only 50 real demonstrations, now open‑sourced after acceptance at RSS 2026.

LingBot-VARSS 2026causal world modeling

0 likes · 5 min read

Enabling Robots to “Think While Acting”: LingBot-VA Paper Accepted at RSS 2026

Machine Learning Algorithms & Natural Language Processing

May 9, 2026 · Artificial Intelligence

Heuristic Learning: Reinforcement Without Parameter Updates via .py File

OpenAI researcher Yong Jiayi introduces Heuristic Learning, a reinforcement paradigm that replaces gradient‑based neural network updates with code‑editing driven by GPT‑5.4, achieving the theoretical 864‑point Atari Breakout score and matching or surpassing PPO on multiple Atari and robot tasks.

Atari BenchmarkContinual LearningGPT-5.4

0 likes · 8 min read

Heuristic Learning: Reinforcement Without Parameter Updates via .py File