Publication Details
Volodymyr Seliuchenko, Lesley De Cruz



Our world is being reshaped by machines which are getting closer to humans in perceptive and cognitive abilities enabling previously unimaginable applications Autonomous cars, mobile home assistant robots, drone delivery networks are just a few examples of the emerging disrupting technologies of this brave new world. Accelerating trends in computational power availability fuel the evolution of artificial intelligence systems which become capable of digesting more and more information that, for systems interacting with the real world, must come from sensors These emerging mobile robotics applications rely heavily on the image and distance sensors to create awareness about their environment the quality of the sensory data, in most cases, determines the key performance parameters and system safety Real applications are often posing the sensory system challenging conditions pushing the sensor specifications to the limits and often calling for novel sensing and signal processing approaches In this work, 2 D and 3 D image sensor systems, the key sensor components of mobile robotics, are discussed Firstly, quantum efficiency improvement methods and a method for dynamic range extension of 4 T image pixels that preserves 4 T pixel dark noise performance are proposed. These quantum efficiency improvement methods and the dynamic range extension method can be applied to both 2 D and 3 D imaging Further, indirect Time of Flight 3 D image sensors are analyzed, and improved 3 D image sensors based on Current Assisted Photonic Demodulators are proposed Finally, a hybrid Time of Flight method that produces a time domain echo signal using photonic demodulator sensor is proposed and compared to direct Time of Flight methods.