Acuity
Technologies
Founded
in 1992, Acuity Technologies develops, manufactures, and
supports specialized unmanned aerial systems for defense
and commercial applications. Experts in aerodynamics,
propulsion systems and in-house design and fabrication,
Acuity offers flight test capabilities to provide complete
UAS life-cycle services. With capabilities for customized
vehicles from single prototypes to production quantities,
Acuity provides operational support and navigation capabilities,
including GPS-denied operation, low-level terrain and
structure avoidance, and video-based waypoint and target
matching software and remote 3D visualization.
Acuity
is also creating imaging systems and software for video
navigation and three dimensional shape, terrain, and indoor
environment capture. This includes equipment and software
with full shape and color capability, and we are bringing
this technology into industrial, marketing, and embedded
applications. Dedicated hardware accelerators for video
rate structure and motion processing can capture over
one million surface points in a single optical flash,
taking microsecond 3D snapshots of objects.
By
combining these technologies, Acuity is developing new
navigation capabilities for UASs, including navigation
in GPS-denied situations, low-level terrain and structure
avoidance, and waypoint and target matching.
UAV
/ UAS
Conventional aircraft design and test cycles are no longer
able to keep up with the rapid change of pace in avionics,
propulsion, sensors, communications, and materials technologies.
By integrating existing subsystems with innovative designs
which plan for the future generations of components, Acuity
quickly and effectively proves air vehicle concepts including
airfames, ground stations, sensors, and diverse payloads.
3D
Terrain and Environment Capture
Acuity's
sensors group is creating imaging systems and software for
video navigation and 3 dimensional shape, terrain, and indoor
environment capture. This includes equipment and software
with full shape and color capability. Dedicated hardware
accelerators for on-line inspection and video-rate and faster
structure and motion processing are also in development.
Our projected pattern photogrammetry systems can capture
milions of points of complex surface information in a single
optical flash, taking microsecond 3D snapshots of objects
in motion and removing the need for targets used in conventional
photogrammetry.
The
bottleneck in the availability of 3D material for autonomous
vehicle navigation and for human and machine analysis, presentation,
and interaction is the acquisition of 3D models from real
world environments and objects. If accurate, photorealistic
renditions can be automatically created with freely moving
cameras this bottleneck can be removed. Applications for
these models can be found in manufacturing and natural resources
utilization, in forensics, in training and simulation, in
modeling and navigation by unmanned vehicles, in product
presentation and evaluation, in AEC as-built capture and
new structure design, and in medical diagnostics and procedures.
Acuity is bringing this technology into industrial, marketing,
and embedded applications.
Lead
Technical Staff
Robert
Clark
President
Robert
received his BS Summa cum Laude from Princeton University
in Aerospace Engineering in 1982 and MS in Digital Control
Systems from Stanford University's Aeronautics and Astronautics
department in 1983. He then spent several years as a software
and electronics engineering consultant specializing in control
systems. He has been Principal Investigator on development
contracts in sensor systems and aeronautical design and
UAV construction and flight test.
Patents
'Cyclogyro Propulsion and Control",
pending
US Patent
5,309,212 “Scanning Rangefinder with Range to Frequency
Conversion”
US Patent 5,585,786 “Optical Tank-Level Gauge”
US Patent 5,648,844 “Laser Liquid Level Gauge with
Diffuser”
US Patent 5,904,870 “Laser Lens Heater”
US Patent 6,624,889 “Triangulation Displacement Sensor”
Publications
R. Clark, M. Lin, C. Taylor, “3D Environment
Capture from Monocular Video and Inertial Data,” Electronic
Imaging, January 2006.
R. Clark,
“A Laser Distance Measurement Sensor for Industry
and Robotics”, Sensors, 6/94
R. Clark,
“Optical Distance Measurement Sensor”, Measurements
and Control, 10/93
Chinmay
Patel
Aerospace
Research Engineer
Dr.
Patel performs aircaft and flight control system design
and development at Acuity. He received his Doctorate and
Master's from Stanford University's Dept. of Aeronautics
and Astronautics with research in energy extraction from
atmospheric turbulence to reduce/eliminate propulsion requirements
for small UAVs. His work included analysis and design of
control laws for energy extraction from atmospheric turbulence
using stochastic optimization techniques and flight tests
conducted on a custom-made UAV and autopilot for validation.
He is the recipient of the Stanford Graduate Fellowship
(SGF), Stanford University’s highest financial award
to graduate students.
Book
Chinmay
Patel, Energy Extraction from Atmospheric Turbulence
to Improve Aircraft Performance, VDM Verlag, 2008.
Conference
Presentations and Technical Publications
Lissaman,
P. B. S., Patel, C. K. [2007], Neutral Energy Cycles for
a Vehicle in Sinusoidal and
Turbulent Vertical Gusts, AIAA paper 2007-0863. 45th AIAA
Aerospace Sciences Meeting and
Exhibit, Reno, NV.
Patel,
C. K., Kroo, I. M. [2006], Control Law Design for Improving
UAV Performance Using Wind
Turbulence, AIAA paper 2006-0231. 44th AIAA Aerospace Sciences
Meeting and Exhibit, Reno, NV.
Rakow,
A., Patel C. K. et. al. [2004], Design, Analysis, Manufacturing
and Testing of a Composite
Smart-Bridge, SAMPE Journal, Vol. 40, No. 5. Member of the
manufacturing team for Stanford
University's winning entry in the 2004 SAMPE Bridge Design
Competition, Long Beach, CA.
Patel,
C. K., Arya, H., Sudhakar, K. [2002], Design, Build and
Fly a Solar Powered Aircraft,
Presented at the International Seminar and Annual General
Meeting of the Aeronautical Society of
India, Goa, India.
Charles
Guo
Staff
Scientist
Dr.
Guo works in Acuity's video processing group on reconstruction
of 3D environment models from video streams. He received
his Ph.D. from UCLA in 2004 in Statistical Image Modeling,
Machine Learning, Pattern Recognition and Computer Vision.
He has performed research in, and developed software using,
Generative/ Descriptive/ Discriminative image modeling,
Bayesian Modeling and Inference, Markov chain Monte Carlo
(MCMC) computing, ML/MAP estimation, HMM, EM, wavelets.
and other methods. Prior to joining Acuity he worked as
a research scientist at Vidient Systems, Sunnyvale, CA on
Intelligent Video Surveillance/Analytics, including GMM
background modeling, shadow and reflection detection, CNN
(Convolutional Neural Network) object detection and recognition,
SVM object recognition, Mean-shift tracking, Blob-based
tracking, optical flow, and Event Extraction from Videos.
Publications
Book
Chapters:
Ying
Nian Wu, Cheng-en Guo, and Song-Chun Zhu, “Perceptual
Scaling”, Applied Bayesian Modeling and Causal Inference
from an Incomplete Data Perspective, Ed. Gelman and Meng,
John Wiley, 2004.
Journal
Articles:
Ying Nian Wu , Song-Chun Zhu, and Cheng-en Guo, “From
Information Scaling of Natural Images to Regimes of Statistical
Models”, Quarterly of Applied Mathematics
Cheng-en Guo,
Song-Chun Zhu, and Ying Nian Wu, “Primal Sketch: Integrating
Structure and Texture” Computer Vision and Image Understanding
Song-Chun Zhu,
Cheng-en Guo, Yizhou Wang, and Zijian Xu, “What are
Textons?”,
International Journal of Computer Vision, Vol. 62, No. 1-2,
pp.121-143, April-May 2005.
Cheng-en
Guo, Song-Chun Zhu, and Ying Nian Wu,
“Modeling Visual Patterns by Integrating Descriptive
and Generative Methods”, International Journal of
Computer Vision, Vol. 53, No. 1, pp.5-29, June 2003.
Jiebo
Luo and Cheng-en Guo, “Perceptual Grouping of Segmented
Regions in Color Images”,
Pattern Recognition, vol. 36, no. 12, pp.2781-2792, December
2003.
Conference
Articles:
Cheng-en
Guo, Ying Nian Wu, and Song-Chun Zhu, “Information
Scaling Laws in Natural Scenes”, Proceedings of 2nd
Workshop on Generative Model Based Vision, Washington DC,
2004.
Cheng-en
Guo, Song-Chun Zhu and Ying Nian Wu, “Towards a Mathematical
Theory of Primal Sketch and Sketchability”, Proc.
of 9th International Conference on Computer Vision, pp.1228-1235,
Nice, France, 2003.
Ying Nian Wu, Song-Chun Zhu and Cheng-en Guo, “Statistical
Modeling of Image Sketch”, Proc. of 7th European Conf.
on Computer Vision, pp.240-254, Copenhagen, Denmark, 2002.
Cheng-en Guo, Song-Chun Zhu and Ying Nian Wu, “Visual
Learning by Integrating Descriptive and Generative Models”,
Proc. of 8th Int’l Conf. on Computer Vision, vol.1
pp. 370-377, Vancouver, Canada, 2001.
Song-Chun
Zhu and Cheng-en Guo, “Conceptualization and Modeling
of Visual Patterns - A Modern Statistical Physics Foundation
for Visual Complexity”, Proc. of Third Workshop on
Perceptual Organization in Computer Vision, Vancouver, Canada,
2001.
Song-Chun
Zhu and Cheng-en Guo, “Mathematical Modeling of Clutter:
descriptive vs. generative models”, Proc. of SPIE
AeroSense Conf. on Automatic Target Recognition, Orlando,
FL, 2000.
Kevin
Ciocia
Lead Mechanical Engineer
Mr.
Ciocia is the lead mechanical engineer on air vehicle and
sensor systems at Acuity. His work here has included developing
advanced propulsion concepts and designing and testing engine
and rotor prototypes. He also led a team that placed in
the top four nationally in the SAE Supermileage Vehicle
Competition four years running, and developed the digitally
controlled fuel injected engine for the car. Mr. Ciocia
holds Bachelor's degrees in Mechanical Engineering and Applied
Mathematics from the University of California at Berkeley.
Robert
Davidson
Hardware Engineer
Mr.
Davidson provides engineering support, for propulsive, mechanical,
and avionics system layout and installation computer on
Acuity's prototype vehicles and sensor systems. Before joining
Acuity he was a Field Engineer for Panasonic Avionics System
Corp assigned to United Air Lines at SFO. In his naval career
Robert served as a weapons system integrator, maintenance
personnel trainer, and P3 Orion aircrew sensor operator
and in-flight technician, with over 4300 flight hours. He
is experienced in all P3-A/B and -C systems including electrical,
avionics, hydraulic, instrumentation, cryptographics, and
signaling.
