This thesis investigates how foundation models can be systematically leveraged to enhance robotic capabilities, enabling more effective localization, interaction, and manipulation in unstructured environments. The work is structured around four core lines of inquiry, each addressing a fundamental challenge in robotics while collectively contributing to a cohesive framework for semantics-aware robotic intelligence.

翻译：本论文系统性地研究了如何利用基础模型来增强机器人能力，使其能够在非结构化环境中实现更有效的定位、交互与操作。研究工作围绕四个核心研究方向展开，每个方向分别应对机器人学中的一个基础性挑战，并共同构建了一个语义感知机器人智能的协同框架。