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Visual Language Models for Long-Term Planning
This project uses Visual Language Models (VLMs) for high-level planning and supervision in construction tasks, enabling task prioritization, dynamic adaptation, and multi-robot collaboration for excavation and site management.
prioritization, dynamic adaptation, and multi-robot collaboration for excavation and site management
Keywords: Visual Language Models, Long-term planning, Robotics
VLMs excel in reasoning and dynamic code generation, making them ideal for tasks like excavation sequencing, obstacle management, and multi-robot coordination. Applications include dynamic trenching, rock field clearing, and safety monitoring. The goal is to deploy VLM-based systems on autonomous excavators to enhance efficiency and adaptability.
VLMs excel in reasoning and dynamic code generation, making them ideal for tasks like excavation sequencing, obstacle management, and multi-robot coordination. Applications include dynamic trenching, rock field clearing, and safety monitoring. The goal is to deploy VLM-based systems on autonomous excavators to enhance efficiency and adaptability.
Develop simulated and real scenarios for VLM-driven planning.
Integrate VLMs into excavation control systems for triggering tasks and code generation.
Benchmark performance in complex planning scenarios.
Develop simulated and real scenarios for VLM-driven planning.
Integrate VLMs into excavation control systems for triggering tasks and code generation.
Benchmark performance in complex planning scenarios.