We developed a cost-effective fish-like Autonomous Underwater Vehicle (AUV) with a sophisticated intelligence. The robot fish, named Fisho, is able to avoid obstacles in a swimming pool, reflecting the usual behavior of a biological fish. As a general rule, a robot captures external stimulus by means of electrical sensors, Fisho has infrared sensors to find the distance to close objects and pressure sensors to estimate its vertical physical position (depth). Its brain is a small-sized 200-MHz Single Board Computer (SBC), that collects information from the sensors and sends decisions to electro-mechanical servos (in order to act on its tail and flippers, thus control its trajectory). Fisho's behavior is signed by its velocity and the vibration mode of its tail. Inspired in real fish, we designed its intelligence with a three-layer Markov chain by means of a full characterization of tasks, purposes and fish-moods. Its design and physical structure is both non-expensive and simple, trying to emulate a real fish, whereas addressing all typical challenges in an AUV. In this paper we discuss Fisho's physical implementation: sensing platforms, electro-mechanical structure and intelligence.