Integrated 2-D Optical Flow Sensor

I present a new focal-plane analog VLSI sensor that estimates optical flow in two visual dimensions. The chip significantly improves previous approaches both with respect to the applied model of optical flow estimation as well as the actual hardware implementation. Its distributed computational architecture consists of an array of locally connected motion units that collectively solve for the unique optimal optical flow estimate. The novel gradient-based motion model assumes visual motion to be translational, smooth and biased. The model guarantees that the estimation problem is computationally well-posed regardless of the visual input. Model parameters can be globally adjusted, leading to a rich output behavior. Varying the smoothness strength, for example, can provide a continuous spectrum of motion estimates, ranging from normal to global optical flow. Unlike approaches that rely on the explicit matching of brightness edges in space or time, the applied gradient-based model assures spatiotemporal continuity on visual information. The non-linear coupling of the individual motion units improves the resulting optical flow estimate because it reduces spatial smoothing across large velocity differences. Extended measurements of a 30x30 array prototype sensor under real-world conditions demonstrate the validity of the model and the robustness and functionality of the implementation

Bio-Inspired Optic Flow Sensors for Artificial Compound Eyes.

Compound eyes in flying insects have been studied to reveal the mysterious cues of vision-based flying mechanisms inside the smallest flying creatures in nature. Especially, researchers in the robotic area have made efforts to transfer the findings into their less than palm-sized unmanned air vehicles, micro-air-vehicles (MAVs). The miniaturized artificial compound eye is one of the key components in this system to provide visual information for navigation. Multi-directional sensing and motion estimation capabilities can give wide field-of-view (FoV) optic flows up to 360 solid angle. By deciphering the wide FoV optic flows, relevant information on the self-status of flight is parsed and utilized for flight command generation. In this work, we realize the wide-field optic flow sensing in a pseudo-hemispherical configuration realized by mounting a number of 2D array optic flow sensors on a flexible PCB module. The flexible PCBs can be bent to form a compound eye shape by origami packaging. From this scheme, the multiple 2D optic flow sensors can provide a modular, expandable configuration to meet low power constraints. The 2D optic flow sensors satisfy the low power constraint by employing a novel bio-inspired algorithm. We have modified the conventional elementary motion detector (EMD), which is known to be a basic operational unit in the insect’s visual pathways. We have implemented a bio-inspired time-stamp-based algorithm in mixed-mode circuits for robust operation. By optimal partitioning of analog to digital signal domains, we can realize the algorithm mostly in digital domain in a column-parallel circuits. Only the feature extraction algorithm is incorporated inside a pixel in analog circuits. In addition, the sensors integrate digital peripheral circuits to provide modular expandability. The on-chip data compressor can reduce the data rate by a factor of 8, so that it can connect a total of 25 optic flow sensors in a 4-wired Serial Peripheral Interface (SPI) bus. The packaged compound eye can transmit full-resolution optic flow data through the single 3MB/sec SPI bus. The fabricated 2D optic flow prototype sensor has achieved the power consumption of 243.3pJ/pixel and the maximum detectable optic flow of 1.96rad/sec at 120fps and 60 FoV.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108841/1/sssjpark_1.pd

Visual Motion Computation in Analog VLSI using Pulses

The real time computation of motion from real images using a single chip with integrated sensors is a hard problem. We present two analog VLSI schemes that use pulse domain neuromorphic circuits to compute motion. Pulses of variable width, rather than graded potentials, represent a natural medium for evaluating temporal relationships. Both algorithms measure speed by timing a moving edge in the image. Our first model is inspired by Reichardt's algorithm in the fly and yields a non-monotonic response vs. velocity curve. We present data from a chip that implements this model. Our second algorithm yields a monotonic response vs. velocity curve and is currently being translated into silicon. 1 Introduction Analog VLSI chips for the real time computation of visual motion have been the focus of much active research because of their importance as sensors for robotic applications. Correlation schemes such as those described in (Delbruck, 1993) have been found to be more robust than gradient s..