Robot Learning | Takato Horii | Osaka University

TARAD: Task-Aware Robot Affordance-Centric Diffusion Policy Learned From LLM-Generated Demonstrations

Wed, 01 Oct 2025 00:00:00 +0000

AI Cobots for Next-Generation Shipyards

Tue, 01 Apr 2025 00:00:00 +0000

Shipyards demand collaborative environments in which humans and robots can work in close proximity without safety barriers. This project develops AI-driven motion acquisition and task execution algorithms for collaborative robots (cobots), contributing to next-generation shipyards that flexibly adapt to complex and diverse shipbuilding processes.

We combine imitation learning, reinforcement learning, and foundation models such as Large Language Models and Vision-Language Models to study frameworks by which robots acquire skills while observing and understanding human work. The goal is to implement general-purpose cobots that can safely cooperate with on-site workers while handling tasks in the long tail of the distribution.

Robot Learning and LLM-Based Action Planning

Mon, 01 Jan 2024 00:00:00 +0000

Research on autonomous action planning and motion generation for robots using imitation learning, reinforcement learning, and Large Language Models (LLMs). We develop state-of-the-art methods including multi-robot task planning combining LLMs and linear programming (LiP-LLM), affordance-centric diffusion policies (TARAD), and humanoid locomotion (LocoGPT).

Robot Learning | Takato Horii | Osaka University

TARAD: Task-Aware Robot Affordance-Centric Diffusion Policy Learned From LLM-Generated Demonstrations

AI Cobots for Next-Generation Shipyards

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Robot Learning and LLM-Based Action Planning