Abstract: Due to their high power-to-weight ratio and low cost, pneumatic actuators are attractive for robotics and automation applications; however, achieving fast and accurate control of their position have been known as a complex control problem. The paper presents a methodology for obtaining controllers that achieve high position accuracy and preserve the closed-loop characteristics over a broad operating range. Experimentation with a number of conventional (or "classical") three-term controllers shows that, as repeated operations accumulate, the characteristics of the pneumatic actuator change requiring frequent re-tuning of the controller parameters (PID gains). Furthermore, three-term controllers are found to perform poorly in recovering the closed-loop system after the application of load or other external disturbances. The key reason for these problems lies in the non-linear exchange of energy inside the cylinder relating, in particular, to the complex friction forces that develop on the piston-wall interface. In order to overcome this problem but still remain within the boundaries of classical control methods, we designed an auto selective classicaql controller so that the system performance would benefit from all three control gains (KP, Kd, Ki) according to system requirements and the characteristics of each type of controller. This challenging experimentation took place for consistent performance in the face of modelling imprecision and disturbances. In the work presented, a selective PID controller is presented for an experimental rig comprising an air cylinder driven by a variable-opening pneumatic valve and equipped with position and pressure sensors. The paper reports on tests carried out to investigate the capability of this specific controller to achieve consistent control performance under, repeated operations and other changes in operating conditions.
Abstract: The work reported in this paper proposes
Swarm-Array computing, a novel technique inspired by swarm
robotics, and built on the foundations of autonomic and parallel
computing. The approach aims to apply autonomic computing
constructs to parallel computing systems and in effect achieve the
self-ware objectives that describe self-managing systems. The
constitution of swarm-array computing comprising four constituents,
namely the computing system, the problem/task, the swarm and the
landscape is considered. Approaches that bind these constituents
together are proposed. Space applications employing FPGAs are
identified as a potential area for applying swarm-array computing for
building reliable systems. The feasibility of a proposed approach is
validated on the SeSAm multi-agent simulator and landscapes are
generated using the MATLAB toolkit.
Abstract: Space exploration is a highly visible endeavour of
humankind to seek profound answers to questions about the origins
of our solar system, whether life exists beyond Earth, and how we
could live on other worlds. Different platforms have been utilized in
planetary exploration missions, such as orbiters, landers, rovers, and
penetrators.
Having low mass, good mechanical contact with the surface,
ability to acquire high quality scientific subsurface data, and ability to
be deployed in areas that may not be conducive to landers or rovers,
Penetrators provide an alternative and complimentary solution that
makes possible scientific exploration of hardly accessible sites (icy
areas, gully sites, highlands etc.).
The Canadian Space Agency (CSA) has put space exploration as
one of the pillars of its space program, and established ExCo program
to prepare Canada for future international planetary exploration.
ExCo sets surface mobility as its focus and priority, and invests
mainly in the development of rovers because of Canada's niche space
robotics technology. Meanwhile, CSA is also investigating how
micro-penetrators can help Canada to fulfill its scientific objectives
for planetary exploration.
This paper presents a review of the micro-penetrator technologies,
past missions, and lessons learned. It gives a detailed analysis of the
technical challenges of micro-penetrators, such as high impact
survivability, high precision guidance navigation and control, thermal
protection, communications, and etc. Then, a Canadian perspective of
a possible micro-penetrator mission is given, including Canadian
scientific objectives and priorities, potential instruments, and flight
opportunities.
Abstract: Evolutionary robotics is concerned with the design of
intelligent systems with life-like properties by means of simulated
evolution. Approaches in evolutionary robotics can be categorized
according to the control structures that represent the behavior and the
parameters of the controller that undergo adaptation. The basic idea
is to automatically synthesize behaviors that enable the robot to
perform useful tasks in complex environments. The evolutionary
algorithm searches through the space of parameterized controllers
that map sensory perceptions to control actions, thus realizing a
specific robotic behavior. Further, the evolutionary algorithm
maintains and improves a population of candidate behaviors by
means of selection, recombination and mutation. A fitness function
evaluates the performance of the resulting behavior according to the
robot-s task or mission. In this paper, the focus is in the use of
genetic algorithms to solve a multi-objective optimization problem
representing robot behaviors; in particular, the A-Compander Law is
employed in selecting the weight of each objective during the
optimization process. Results using an adaptive fitness function show
that this approach can efficiently react to complex tasks under
variable environments.
Abstract: In this paper, we present optimal control for
movement and trajectory planning for four degrees-of-freedom robot
using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have
evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs)
for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like;
Movement, Friction and Settling Time in robotic arm movement
have been compensated using Fuzzy logic and Genetic Algorithms.
The development of a fuzzy genetic optimization algorithm is
presented and discussed. The result are compared only GA and
Fuzzy GA. This paper describes genetic algorithms, which is
designed to optimize robot movement and trajectory. Though the
model represents is a general model for redundant structures and
could represent any n-link structures. The result is a complete
trajectory planning with Fuzzy logic and Genetic algorithms
demonstrating the flexibility of this technique of artificial
intelligence.
Abstract: This paper presents recent work on the improvement
of the robotics vision based control strategy for underwater pipeline
tracking system. The study focuses on developing image processing
algorithms and a fuzzy inference system for the analysis of the
terrain. The main goal is to implement the supervisory fuzzy learning
control technique to reduce the errors on navigation decision due to
the pipeline occlusion problem. The system developed is capable of
interpreting underwater images containing occluded pipeline, seabed
and other unwanted noise. The algorithm proposed in previous work
does not explore the cooperation between fuzzy controllers,
knowledge and learnt data to improve the outputs for underwater
pipeline tracking. Computer simulations and prototype simulations
demonstrate the effectiveness of this approach. The system accuracy
level has also been discussed.
Abstract: This article presents a simple way to perform programmed voice commands for the interface with commercial Digital and Analogue Input/Output PCI cards, used in Robotics and Automation applications. Robots and Automation equipment can "listen" to voice commands and perform several different tasks, approaching to the human behavior, and improving the human- machine interfaces for the Automation Industry. Since most PCI Digital and Analogue Input/Output cards are sold with several DLLs included (for use with different programming languages), it is possible to add speech recognition capability, using a standard speech recognition engine, compatible with the programming languages used. It was created in this work a Visual Basic 6 (the world's most popular language) application, that listens to several voice commands, and is capable to communicate directly with several standard 128 Digital I/O PCI Cards, used to control complete Automation Systems, with up to (number of boards used) x 128 Sensors and/or Actuators.
Abstract: The project describes the modeling of various
architectures mechatronics specifically morphologies of robots in an educational environment. Each structure developed by students of
pre-school, primary and secondary was created using the concept of
reverse engineering in a constructivist environment, to later be integrated in educational software that promotes the teaching of
educational Robotics in a virtual and economic environment.
Abstract: Deployment of pneumatic muscles in various
industrial applications is still in its early days, considering the relative
newness of these components. The field of robotics holds particular
future potential for pneumatic muscles, especially in view of their
specific behaviour known as compliance. The paper presents and
discusses an innovative constructive solution for a gripper system
mountable on an industrial robot, based on actuation by a linear
pneumatic muscle and transmission of motion by gear and rack
mechanism. The structural, operational and constructive models of
the new gripper are presented, along with some of the experimental
results obtained subsequently to the testing of a prototype. Further
presented are two control variants of the gripper system, one by
means of a 3/2-way fast-switching solenoid valve, the other by means
of a proportional pressure regulator. Advantages and disadvantages
are discussed for both variants.
Abstract: Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.
Abstract: The autonomous mobile robot was designed and implemented which was capable of navigating in the industrial environments and did a job of picking objects from variable height and delivering it to another location following a predefined trajectory. In developing country like Bangladesh industrial robotics is not very prevalent yet, due to the high installation cost. The objective of this project was to develop an autonomous mobile robot for industrial application using the available resources in the local market at lower manufacturing cost. The mechanical system of the robot was comprised of locomotion, gripping and elevation system. Grippers were designed to grip objects of a predefined shape. Cartesian elevation system was designed for vertical movement of the gripper. PIC18F452 microcontroller was the brain of the control system. The prototype autonomous robot was fabricated for relatively lower load than the industry and the performance was tested in a virtual industrial environment created within the laboratory to realize the effectiveness.
Abstract: In its attempt to offer new ways into autonomy for a
large population of disabled people, assistive technology has largely
been inspired by robotics engineering. Recent human-like robots
carry new hopes that it seems to us necessary to analyze by means of
a specific theory of anthropomorphism. We propose to distinguish a
functional anthropomorphism which is the one of actual wheelchairs
from a structural anthropomorphism based on a mimicking of human
physiological systems. If functional anthropomorphism offers the
main advantage of eliminating the physiological systems
interdependence issue, the highly link between the robot for disabled
people and their human-built environment would lead to privilege in
the future the anthropomorphic structural way. In this future
framework, we highlight a general interdependence principle : any
partial or local structural anthropomorphism generates new
anthropomorphic needs due to the physiological systems
interdependency, whose effects can be evaluated by means of
specific anthropomorphic criterions derived from a set theory-based
approach of physiological systems.
Abstract: In recent years, IT convergence technology has been developed to get creative solution by combining robotics or sports science technology. Object detection and recognition have mainly applied to sports science field that has processed by recognizing face and by tracking human body. But object detection and recognition using vision sensor is challenge task in real world because of illumination. In this paper, object detection and recognition using vision sensor applied to sports simulator has been introduced. Face recognition has been processed to identify user and to update automatically a person athletic recording. Human body has tracked to offer a most accurate way of riding horse simulator. Combined image processing has been processed to reduce illumination adverse affect because illumination has caused low performance in detection and recognition in real world application filed. Face has recognized using standard face graph and human body has tracked using pose model, which has composed of feature nodes generated diverse face and pose images. Face recognition using Gabor wavelet and pose recognition using pose graph is robust to real application. We have simulated using ETRI database, which has constructed on horse riding simulator.
Abstract: The design of an active leg orthosis for tumble
protection is proposed in this paper. The orthosis would be applied to
assist elders or invalids in rebalancing while they fall unexpectedly.
We observe the regain balance motion of healthy and youthful people,
and find the difference to elders or invalids. First, the physical model
of leg would be established, and we consider the leg motions are
achieve through four joints (phalanx stem, ankle, knee, and hip joint)
and five links (phalanges, talus, tibia, femur, and hip bone). To
formulate the dynamic equations, the coordinates which can clearly
describe the position in 3D space are first defined accordance with the
human movement of leg, and the kinematics and dynamics of the leg
movement can be formulated based on the robotics. For the purpose,
assisting elders and invalids in avoiding tumble, the posture variation
of unbalance and regaining balance motion are recorded by the
motion-capture image system, and the trajectory is taken as the desire
one. Then we calculate the force and moment of each joint based on
the leg motion model through programming MATLAB code. The
results would be primary information of the active leg orthosis design
for tumble protection.
Abstract: One of the long standing challenging aspect in mobile robotics is the ability to navigate autonomously, avoiding modeled and unmodeled obstacles especially in crowded and unpredictably changing environment. A successful way of structuring the navigation task in order to deal with the problem is within behavior based navigation approaches. In this study, Issues of individual behavior design and action coordination of the behaviors will be addressed using fuzzy logic. A layered approach is employed in this work in which a supervision layer based on the context makes a decision as to which behavior(s) to process (activate) rather than processing all behavior(s) and then blending the appropriate ones, as a result time and computational resources are saved.
Abstract: Describes the current situation of educational Robotics
"the State of the art" its concept, its evolution their niches of
opportunity, academic and business and the importance of education
and academic outreach. It shows that the development of high-tech
automated educational materials influence the teaching-learning
process and that communication between machines and humans is a
reality.
Abstract: Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.
Abstract: Developing techniques for mobile robot navigation constitutes one of the major trends in the current
research on mobile robotics. This paper develops a local
model network (LMN) for mobile robot navigation. The
LMN represents the mobile robot by a set of locally valid
submodels that are Multi-Layer Perceptrons (MLPs).
Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular
region. The submodels then are combined in a unified
structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This
proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the
proposed LMN reflect the soundness of the proposed
scheme.
Abstract: This paper presents the development of a software
application for Off-line robot task programming and simulation. Such
application is designed to assist in robot task planning and to direct
manipulator motion on sensor based programmed motion. The
concept of the designed programming application is to use the power
of the knowledge base for task accumulation. In support of the
programming means, an interactive graphical simulation for
manipulator kinematics was also developed and integrated into the
application as the complimentary factor to the robot programming
media. The simulation provides the designer with useful,
inexpensive, off-line tools for retain and testing robotics work cells
and automated assembly lines for various industrial applications.
Abstract: In this work a visual and reactive contour following
behaviour is learned by reinforcement. With artificial vision the
environment is perceived in 3D, and it is possible to avoid obstacles
that are invisible to other sensors that are more common in mobile
robotics. Reinforcement learning reduces the need for intervention in
behaviour design, and simplifies its adjustment to the environment,
the robot and the task. In order to facilitate its generalisation to other
behaviours and to reduce the role of the designer, we propose a
regular image-based codification of states. Even though this is much
more difficult, our implementation converges and is robust. Results
are presented with a Pioneer 2 AT on a Gazebo 3D simulator.