In a rapid serial visual presentation (RSVP) images are shown at an extremely rapid pace. Yet, the images can still be parsed by the visual system to some extent. In fact, the detection of specific targets in a stream of pictures triggers a characteristic electroencephalography (EEG) response that can be recognized by a brain-computer interface (BCI) and exploited for automatic target detection. Research funded by DARPA's Neurotechnology for Intelligence Analysts program has achieved speed-ups in sifting through satellite images when adopting this approach. This paper extends the use of BCI technology from individual analysts to collaborative BCIs. We show that the integration of information in EEGs collected from multiple operators results in performance improvements compared to the single-operator case.
Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-offreedom
(DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and
vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility
conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by
pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for
robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement
unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands
from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The
BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on
dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static
and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and
group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot
behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.
This paper introduces a person identification system that uses as input the shadow images of a walking person, as
projected by multiple lights(in this application invisible/infrared lights); the system uses a database of examples
of shadows images of a number of people who walk. While it is accepted that personal identification has a
higher correct classification rate if views from multiple cameras are used, most systems use only one camera,
mainly because (i) Installation in real-world environments is easier, less cameras and no need to synchronize
cameras, (ii) Computational cost is reduced. In the proposed system, we obtain the advantages of multiple
viewpoints with a single camera and additional light sources. More specific, we install multiple infrared lights
to project shadows of a subject on the ground and a camera with an infrared transmitting filter mounted in
the ceiling inside of a building. Shadow areas, which are projections of one's body on the ground by multiple
lights, can be considered as body areas captured from different viewpoints; thus, the proposed system is able
to capture multiple projections of the body from a single camera. We explored in other papers the use of sunproduced
shadow for identification of people walking freely in the outdoor. In this paper the application scenario
is a system installed at the airport in the areas that precedes the immigration checkpoint. Japan already has
health monitoring cameras focused on approaching individuals, to determine their health condition; the here
described system would also be installed in such a controlled area with restricted walk corridors of walk and
controlled lighting. Gait is a remote biometrics and can provide early warning; on another hand it can be used
as corroborating evidence in a multi-modal biometrics system. A database of images including shadows for a set
of 28 walking people was collected, and the features extracted from shadow areas by affine moment invariants,
after which identification of the subject followed. The experiments using the database show the effectiveness
of the proposed method and further prove the superiority of using multiple viewpoints compared to a single
viewpoint.
KEYWORDS: Robots, Robotics, Space robots, Sensors, Space operations, Control systems, Algorithm development, Cognitive modeling, Sensing systems, Robotic systems
Cognitive robots in the context of space exploration are envisioned with advanced capabilities of model building,
continuous planning/re-planning, self-diagnosis, as well as the ability to exhibit a level of 'understanding' of new
situations. An overview of some JPL components (e.g. CASPER, CAMPOUT) and a description of the architecture
CARACaS (Control Architecture for Robotic Agent Command and Sensing) that combines these in the context of a
cognitive robotic system operating in a various scenarios are presented. Finally, two examples of typical scenarios of a
multi-robot construction mission and a human-robot mission, involving direct collaboration with humans is given.
Real-time evolvable systems are possible with a hardware implementation of Genetic Algorithms (GA). We report the
design of an IP core that implements a general purpose GA engine which has been successfully synthesized and verified
on a Xilinx Virtex II Pro FPGA Device (XC2VP30). The placed and routed IP core has an area utilization of only 13%
and clock speed of 50MHz. The GA core can be customized in terms of the population size, number of generations,
cross-over and mutation rates, and the random number generator seed. The GA engine can be tailored to a given
application by interfacing with the application specific fitness evaluation module as well as the required storage memory
(to store the current and new populations). The core is soft in nature i.e., a gate-level netlist is provided which can be
readily integrated with the user's system. The GA IP core can be readily used in FPGA based platforms for space and
military applications (for e.g., surveillance, target tracking). The main advantages of the IP core are its programmability,
small footprint, and low power consumption. Examples of concept systems in sensing and surveillance domains will be
presented.
The rapid advancements in ad hoc sensor networks, MEMS (micro-electro-mechanical systems) devices, low-power
electronics, adaptive hardware and systems (AHS), reconfigurable architectures, high-performance computing platforms,
distributed operating systems, micro-spacecrafts, and micro-sensors have enabled the design and development of a highperformance
satellite sensor network (SSN). Due to the changing environment and the varying missions that a SSN may
have, there is an increasing need to develop efficient strategies to design, operate, and manage the system at different
levels from an individual satellite node to the whole network. Towards this end, this paper presents an adaptive
approach to space-based picosatellite sensor network by exploiting efficient bio-inspired optimization algorithms,
particularly for solving multi-objective optimization problems at both local (node) and global (network) system levels.
The proposed approach can be hierarchically used for dealing with the challenging optimization problems arising from
the energy-constrained satellite sensor networks. Simulation results are provided to demonstrate the effectiveness of the
proposed approach through its application in solving both node-level and system-level optimization problems.
This paper addresses the problem of quality assessment dedicated to two important applications : image compression and watermarking. This topic is nowadays of a great interest because of the limitations of the mathematical criteria used formerly for quality assessment. The main aspect of this paper is the use of psychophysical experiences
in order to take into account the capacities of the Human Visual System. Two campaigns have been taken for assess quality for both compression and watermarking. The main conclusion of this work is that the metrics used to assess quality such as the PSNR are very far from the human judgment and consequently from the real assessment.
KEYWORDS: Fuzzy logic, Analog electronics, Sensor fusion, Neural networks, Neurons, Sensors, Signal processing, Very large scale integration, Rule based systems, Intelligent sensors
The paper present the concept and initial test from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics an autonomous system are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an 'intelligent' processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.