Vision-Language-Action Models: Concepts, Progress, Applications and
  Challenges
Authors: name: Ranjan Sapkota, name: Yang Cao, name: Konstantinos I. Roumeliotis, name: Manoj Karkee

Vision-Language-Action (VLA) models mark a transformative advancement in
artificial intelligence, aiming to unify perception, natural language
understanding, and embodied action within a single computational framework.
This foundational review presents a comprehensive synthesis of recent
advancements in Vision-Language-Action models, systematically organized across
five thematic pillars that structure the landscape of this rapidly evolving
field. We begin by establishing the conceptual foundations of VLA systems,
tracing their evolution from cross-modal learning architectures to generalist
agents that tightly integrate vision-language models (VLMs), action planners,
and hierarchical controllers. Our methodology adopts a rigorous literature
review framework, covering over 80 VLA models published in the past three
years. Key progress areas include architectural innovations,
parameter-efficient training strategies, and real-time inference accelerations.
We explore diverse application domains such as humanoid robotics, autonomous
vehicles, medical and industrial robotics, precision agriculture, and augmented
reality navigation. The review further addresses major challenges across
real-time control, multimodal action representation, system scalability,
generalization to unseen tasks, and ethical deployment risks. Drawing from the
state-of-the-art, we propose targeted solutions including agentic AI
adaptation, cross-embodiment generalization, and unified neuro-symbolic
planning. In our forward-looking discussion, we outline a future roadmap where
VLA models, VLMs, and agentic AI converge to power socially aligned, adaptive,
and general-purpose embodied agents. This work serves as a foundational
reference for advancing intelligent, real-world robotics and artificial general
intelligence. >Vision-language-action, Agentic AI, AI Agents, Vision-language
Models