<p>In this paper, an autonomous intelligent transportation robot equipped with intelligent perception and autonomous planning modules is proposed to meet the requirements of roll-on/roll-off (RO/RO) logistics terminals for the autonomous transportation of various types of finished vehicles. Based on the robot operating system (ROS) framework and a modular design approach, the robot integrates several key components, including a visual perception module, an autonomous planning module, a motion control module, an execution module, and an energy module. First, an improved convex hull algorithm efficiently extracts point cloud data, enhancing the efficiency of point cloud processing and addressing the issue of excessive target data. Three different evaluation methods were employed to determine the optimal bounding box of the target vehicle and to obtain its pose state. Second, improved proximal policy optimization (PPO) and generalized advantage estimation (GAE) algorithms, which are utilized in this paper, were implemented to autonomously plan collisionfree trajectories for robots, facilitating their movement from an initial position to the target transportation location, and subsequently to the final placement position. Finally, physical experiments confirmed that the robot effectively mimics the three fundamental components of humanoid functionality: perception, cognition, and action, thus enabling autonomous and intelligent handling of complex vehicle transportation tasks. These demonstrations validate the feasibility and effectiveness of the proposed robot.</p>