By combining ultrasonic imaging with neural networks, the authors have developed a 3-D object recognition system for use in robotic vision. Ultrasonic imaging is used to calculate the initial 3-D images of the objects. These images are then passed to neural networks that identify object categories, estimate object locations, and improve 3-D images. The authors explain the 3-D ultrasonic imaging method, propose three neural network structures for 3-D image analysis, and demonstrate the practicability of the system through experimental results, which show that quick and accurate recognition can be achieved using only a small set of transducers