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In this paper, we propose a driving system consisting of an autonomous and manual system for a four-wheel independent steering and four-wheel independent driving (4WIS4WID) vehicle. The autonomous driving system consists of three applications, lane following, reverse parking, and parallel parking, and is based on machine vision and fuzzy control theory. The vehicle implements these functions by using four webcams to detect lines on the ground and by using related control technologies to command all the server motors. The webcams are installed on all sides of the 4WIS4WID vehicle for all around viewing, but the vehicle still has many blind spots and the view is not wide enough. In additon, a parking space cannot be viewed completely in one image. Therefore, the integrating judgements of vision with the fuzzy control methods is necessary to make sure that the 4WIS4WID vehicle can perform the correct motions. By using the proposed fuzzy rules, the 4WIS4WID vehicle can change its velocity in a timely way under any condition and can successfully move in a narrow and curved lane. Moreover, the manual driving system is designed based on the traditional driving system, so that people can easily adapt to it. In order to verify the feasibility of these applications for the 4WIS4WID vehicle, an indoor real-time experiment is conducted.

Can a robot think like a human being? Scientists in recent years have been trying to achieve this dream, and we are also committed to this same goal. In this paper, we use an example of throwing the ball into the basket to make the robots process with human-like thinking behavior. Such thinking behavior adopted in this paper is divided into two modes: fast and slow. The fast mode belongs to the intuitional reaction, and the slow mode represents the complicated cogitation in human brain. This fascinating human thinking concept is inspired by the book, Thinking, Fast and Slow , which explains the process of the human brain. In addition, the psychology theories proposed in this book are also adopted to realize the thinking algorithms, and our experiments verify that the thinking mode of human beings is reasonable and effective in robots.