TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics

Researchers have developed TIGeR, a framework that enhances Vision-Language Models with precise geometric reasoning capabilities for robotics applications. The system enables VLMs to execute centimeter-level accurate computations by integrating external computational tools, moving beyond qualitative spatial reasoning to quantitative precision required for real-world robotic manipulation.

• →TIGeR transforms Vision-Language Models from perceptual estimators to geometric computers capable of precise calculations.
• →The framework addresses current VLMs' limitation of lacking computational precision needed for real-world robotics applications.
• →TIGeR-300K dataset provides comprehensive tool-invocation training data covering point transformations, pose estimation, and spatial verification.
• →The system achieves state-of-the-art performance on geometric reasoning benchmarks with centimeter-level precision.
• →Two-stage training pipeline combines supervised and reinforcement fine-tuning with hierarchical reward design for optimal performance.