An autonomous actor, whether biological, mechatronic, or biomechatronic, whether flying, wheeled, or walking, requires sensory information to characterize, navigate through, and interact with its environment. One of the most critical types of information for tasks such as path/route planning, obstacle avoidance, and object manipulation is depth, or distance to objects in the environment. An ideal depth sensor would be small, lightweight, low power, provide frequent updates, and have a high resolution in all three spatial axes. Robots and other actors, including human-controlled, remotely operated devices, use a variety of depth-sensing techniques, including stereo vision, LIDAR/RADAR (light/radio detection and ranging), sonar (sound navigation and ranging), and tactile interaction.
The choice of sensor is determined by metrics such as size, mass, power consumption, spatiotemporal resolution, as well as the difficulty of integrating the sensor into the “user” host device. Pairs of cameras used for stereo vision, like other types of vision sensors, generate high bandwidth moving images and require significant signal processing to solve the stereo correspondence problem to provide usable depth information; the bandwidth of the sensor output far exceeds the bandwidth of useful data that it provides. The motivation of this work is the integration of stereo vision imagers (cameras) and computation into a single sensor that provides low bandwidth digital depth information output.
This work presents two generations of a Single-chip Stereo Imager (SSI), a single integrated circuit (IC) including both imagers and depth computation circuitry. Compared to traditional two-camera and digital processor solutions, the integration of stereo sensing and processing onto a single IC offers the advantages of reduced size, weight, and power consumption, as well as simplified integration with larger systems. Results from the two SSI sensors, as well as descriptions of the circuits required to create the sensors, are described.
|School:||The Johns Hopkins University|
|School Location:||United States -- Maryland|
|Source:||DAI-B 69/12, Dissertation Abstracts International|
|Keywords:||Active pixel sensors, CMOS, Image sensors, Single-chip stereo imaging|
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