SBIR Phase I: GHz Time-of-Flight Depth Sensing for Robotic Bin Picking

The broader impact/commercial impact of this project will be to create a depth vision system that accelerates the transition to intelligent automation. The intelligent automation movement is driven by the opportunity to increase human productivity, and it can be seen in all domains: from Siemen?s self-organizing manufacturing plants to Amazon?s proposed delivery drones. This project aims to improve robotic vision, which is currently a limitation to greater autonomy. The research uses innovations in semiconductor physics to create time-of-flight depth cameras that reach new levels of spatial resolution and fidelity. These cameras, in conjunction with rapidly evolving software that uses depth data to model the physical world, give robotic systems the human-like abilities they need to perform more complicated tasks in dynamic environments. Robotics will become increasingly effective at the navigation, material handling, and object manipulation tasks that are the basis of so many manufacturing and logistics processes. The project outcomes will advance the state-of-the-art in depth vision technology, and provide a prototype camera that can be used to test a variety of challenging object recognition tasks. This Small Business Innovation Research (SBIR) Phase I project addresses an important limitation in depth cameras that use the phase delay time-of-flight (TOF) method. Existing TOF cameras use ?pixel-level demodulation?: specially designed photodetector arrays where each pixel performs both light detection and demodulation. This design limits the modulation frequency, and thus depth accuracy, because the high frequency signals create excessive noise and parasitic capacitances. The authors propose an alternative ?optical demodulation? design wherein light is demodulated by a single fast optical shutter, and then collected by a separate conventional image sensor. By separating light modulation from light detection, parasitic capacitances are eliminated and it is possible to reach high frequencies with acceptable power consumption and noise. The research program will develop new optical shutters that demonstrate these characteristics, and integrate the shutters into a functioning prototype depth camera. Success will show that TOF cameras can be produced with substantially higher spatial resolution and design flexibility.