This research introduces CoT-VLA, a novel approach that enables robots to perform complex manipulation tasks through step-by-step visual reasoning rather than direct input-output mappings.

• Integrates chain-of-thought reasoning into vision-language-action models
• Improves robot performance on complex manipulation tasks requiring temporal planning
• Demonstrates significant performance gains over existing approaches
• Enables robots to explain their reasoning process during task execution

For engineering applications, this advancement represents a crucial step toward more capable robots that can handle real-world complexity through deliberate reasoning rather than simple reactive behaviors.

CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models