Abstract: Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.
Abstract: We present a hardware oriented method for real-time
measurements of object-s position in video. The targeted application
area is light spots used as references for robotic navigation. Different
algorithms for dynamic thresholding are explored in combination
with component labeling and Center Of Gravity (COG) for highest
possible precision versus Signal-to-Noise Ratio (SNR). This method
was developed with a low hardware cost in focus having only one
convolution operation required for preprocessing of data.
Abstract: In modern day disaster recovery mission has become
one of the top priorities in any natural disaster management regime.
Smart autonomous robots may play a significant role in such
missions, including search for life under earth quake hit rubbles,
Tsunami hit islands, de-mining in war affected areas and many other
such situations. In this paper current state of many walking robots are
compared and advantages of hexapod systems against wheeled robots
are described. In our research we have selected a hexapod spider
robot; we are developing focusing mainly on efficient navigation
method in different terrain using apposite gait of locomotion, which
will make it faster and at the same time energy efficient to navigate
and negotiate difficult terrain. This paper describes the method of
terrain negotiation navigation in a hazardous field.
Abstract: Recently, the Spherical Motion Models (SMM-s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM-s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their performances of the SMM-s, the most powerful tools of estimation theory, the extended Kalman filter (EKF) and unscented Kalman filter (UKF), which give the best estimations in noisy environments, have been employed. The Monte Carlo validation implementations used to test the stability and robustness of the models have been employed as well.
Abstract: This paper deals with motion planning of multiple
mobile robots. Mobile robots working together to achieve several
objectives have many advantages over single robot system. However,
the planning and coordination between the mobile robots is
extremely difficult. In the present investigation rule-based and rulebased-
neuro-fuzzy techniques are analyzed for multiple mobile
robots navigation in an unknown or partially known environment.
The final aims of the robots are to reach some pre-defined goals.
Based upon a reference motion, direction; distances between the
robots and obstacles; and distances between the robots and targets;
different types of rules are taken heuristically and refined later to find
the steering angle. The control system combines a repelling influence
related to the distance between robots and nearby obstacles and with
an attracting influence between the robots and targets. Then a hybrid
rule-based-neuro-fuzzy technique is analysed to find the steering
angle of the robots. Simulation results show that the proposed rulebased-
neuro-fuzzy technique can improve navigation performance in
complex and unknown environments compared to this simple rulebased
technique.
Abstract: We present a BeeBot, Binus Multi-client Intelligent Telepresence Robot, a custom-build robot system specifically designed for teleconference with multiple person using omni directional actuator. The robot is controlled using a computer networks, so the manager/supervisor can direct the robot to the intended person to start a discussion/inspection. People tracking and autonomous navigation are intelligent features of this robot. We build a web application for controlling the multi-client telepresence robot and open-source teleconference system used. Experimental result presented and we evaluated its performance.
Abstract: This paper presents a solution for the behavioural
animation of autonomous virtual agent navigation in virtual environments.
We focus on using Dempster-Shafer-s Theory of Evidence
in developing visual sensor for virtual agent. The role of the visual
sensor is to capture the information about the virtual environment
or identifie which part of an obstacle can be seen from the position
of the virtual agent. This information is require for vitual agent to
coordinate navigation in virtual environment. The virual agent uses
fuzzy controller as a navigation system and Fuzzy α - level for
the action selection method. The result clearly demonstrates the path
produced is reasonably smooth even though there is some sharp turn
and also still not diverted too far from the potential shortest path.
This had indicated the benefit of our method, where more reliable
and accurate paths produced during navigation task.
Abstract: In this work, a new approach is proposed to control
the manipulators for Humanoid robot. The kinematics of the
manipulators in terms of joint positions, velocity, acceleration and
torque of each joint is computed using the Denavit Hardenberg (D-H)
notations. These variables are used to design the manipulator control
system, which has been proposed in this work. In view of supporting
the development of a controller, a simulation of the manipulator is
designed for Humanoid robot. This simulation is developed through
the use of the Virtual Reality Toolbox and Simulink in Matlab. The
Virtual Reality Toolbox in Matlab provides the interfacing and
controls to an environment which is developed based on the Virtual
Reality Modeling Language (VRML). Chains of bones were used to
represent the robot.
Abstract: Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.
Abstract: The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.
Abstract: Website plays a significant role in success of an e-business. It is the main start point of any organization and corporation for its customers, so it's important to customize and design it according to the visitors' preferences. Also, websites are a place to introduce services of an organization and highlight new service to the visitors and audiences. In this paper, we will use web usage mining techniques, as a new field of research in data mining and knowledge discovery, in an Iranian government website. Using the results, a framework for web content layour is proposed. An agent is designed to dynamically update and improve web links locations and layout. Then, we will explain how it is used to directly enable top managers of the organization to influence on the arrangement of web contents and also to enhance customization of web site navigation due to online users' behaviors.
Abstract: The dynamics of the Autonomous Underwater
Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate
accurately because of the variations of these coefficients with
different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain
the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line
adaptive fuzzy model and adaptive neural fuzzy network (ANFN)
model techniques to overcome the uncertain external disturbance and
the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according
to the back propagation algorithm based upon the error between the
identified model and the actual output of the plant. The proposed
ANFN model adopts a functional link neural network (FLNN) as the
consequent part of the fuzzy rules. Thus, the consequent part of the
ANFN model is a nonlinear combination of input variables. Fuzzy
control system is applied to guide and control the AUV using both
adaptive models and mathematical model. Simulation results show
the superiority of the proposed adaptive neural fuzzy network
(ANFN) model in tracking of the behavior of the AUV accurately
even in the presence of noise and disturbance.
Abstract: This paper introduces a low cost INS/GPS algorithm for
land vehicle navigation application. The data fusion process is done
with an extended Kalman filter in cascade configuration mode. In
order to perform numerical simulations, MATLAB software has been
developed. Loosely coupled configuration is considered. The results
obtained in this work demonstrate that a low-cost INS/GPS navigation
system is partially capable of meeting the performance requirements
for land vehicle navigation. The relative effectiveness of the kalman
filter implementation in integrated GPS/INS navigation algorithm is
highlighted. The paper also provides experimental results; field test
using a car is carried out.
Abstract: Recently research on human wayfinding has focused
mainly on mental representations rather than processes of
wayfinding. The objective of this paper is to demonstrate the
rationality behind applying multi-agent simulation paradigm to the
modeling of rescuer team wayfinding in order to develop
computational theory of perceptual wayfinding in crisis situations
using image schemata and affordances, which explains how people
find a specific destination in an unfamiliar building such as a
hospital. The hypothesis of this paper is that successful navigation is
possible if the agents are able to make the correct decision through
well-defined cues in critical cases, so the design of the building
signage is evaluated through the multi-agent-based simulation. In
addition, a special case of wayfinding in a building, finding one-s
way through three hospitals, is used to demonstrate the model.
Thereby, total rescue time for rescue operation during building fire is
computed. This paper discuses the computed rescue time for various
signage localization and provides experimental result for
optimization of building signage design. Therefore the most
appropriate signage design resulted in the shortest total rescue time in
various situations.
Abstract: Recognizing human action from videos is an active
field of research in computer vision and pattern recognition. Human
activity recognition has many potential applications such as video
surveillance, human machine interaction, sport videos retrieval and
robot navigation. Actually, local descriptors and bag of visuals words
models achieve state-of-the-art performance for human action
recognition. The main challenge in features description is how to
represent efficiently the local motion information. Most of the
previous works focus on the extension of 2D local descriptors on 3D
ones to describe local information around every interest point. In this
paper, we propose a new spatio-temporal descriptor based on a spacetime
description of moving points. Our description is focused on an
Accordion representation of video which is well-suited to recognize
human action from 2D local descriptors without the need to 3D
extensions. We use the bag of words approach to represent videos.
We quantify 2D local descriptor describing both temporal and spatial
features with a good compromise between computational complexity
and action recognition rates. We have reached impressive results on
publicly available action data set
Abstract: This paper discusses the implementation of the Kalman
Filter along with the Global Positioning System (GPS) for indoor
robot navigation. Two dimensional coordinates is used for the map
building, and refers to the global coordinate which is attached to the
reference landmark for position and direction information the robot
gets. The Discrete Kalman Filter is used to estimate the robot position,
project the estimated current state ahead in time through time update
and adjust the projected estimated state by an actual measurement at
that time via the measurement update. The navigation test has been
performed and has been found to be robust.
Abstract: Route bus system is the fundamental public transportation
system and has an important role in every province. To improve
the usability of it greatly, we develop an AR application for "Bus-
Net". The Bus-Net system is the shortest path planning system.
Bus-Net supports bus users to make a plan to change buses by
providing them with information about the direction. However, with
Bus-Net, these information are provided in text-base. It is difficult
to understand them for the person who does not know the place. We
developed the AR application for Bus-Net. It supports the action of
a bus user in an innovative way by putting information on a camera
picture and leading the way to a bus stop. The application also inform
the user the correct bus to get, the direction the bus takes and the
fare, which ease many anxieties and worries people tend to feel when
they take buses.
Abstract: An accident is an unexpected and unplanned situation
that happens and affects human in a negative outcome. The accident
can cause an injury to a human biological organism. Thus, the
provision of initial care for an illness or injury is very important
move to prepare the patients/victims before sending to the doctor. In
this paper, a First Aid Application is developed to give some
directions for preliminary taking care of patient/victim via Android
mobile device. Also, the navigation function using Google Maps API
is implemented in this paper for searching a suitable path to the
nearest hospital. Therefore, in the emergency case, this function can
be activated and navigate patients/victims to the hospital with the
shortest path.
Abstract: Nowadays, driving support systems, such as car
navigation systems, are getting common, and they support drivers in
several aspects. It is important for driving support systems to detect
status of driver's consciousness. Particularly, detecting driver's
drowsiness could prevent drivers from collisions caused by drowsy
driving. In this paper, we discuss the various artificial detection
methods for detecting driver's drowsiness processing technique. This
system is based on facial images analysis for warning the driver of
drowsiness or in attention to prevent traffic accidents.
Abstract: The paper researched and presented a virtual simulation system based on a full-digital lunar terrain, integrated with kinematics and dynamics module as well as autonomous navigation simulation module. The system simulation models are established. Enabling technologies such as digital lunar surface module, kinematics and dynamics simulation, Autonomous navigation are investigated. A prototype system for lunar rover locomotion simulation is developed based on these technologies. Autonomous navigation is a key echnology in lunar rover system, but rarely involved in virtual simulation system. An autonomous navigation simulation module have been integrated in this prototype system, which was proved by the simulation results that the synthetic simulation and visualizing analysis system are established in the system, and the system can provide efficient support for research on the autonomous navigation of lunar rover.