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: 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: 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: 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: 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: 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: 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 recent development of humanoid robots has led robot designers to imagine a great variety of anthropomorphic forms for human-like machine. Which form is the best ? We try to answer this question from a double meaning of the anthropomorphism : a positive anthropomorphism corresponing to the realization of an effective anthropomorphic form object and a negative one corresponding to our natural tendency in certain circumstances to give human attributes to non-human beings. We postulate that any humanoid robot is concerned by both these two anthropomorphism kinds. We propose to use gestalt theory and Heider-s balance theory in order to analyze how negative anthropomorphism can influence our perception of human-like robots. From our theoretical approach we conclude that an “even shape" as defined by gestalt theory is not a sufficient condition for a good integration of future humanoid robots into a human community. Aesthetic perception of the robot cannot be splitted from a social perception : a humanoid robot, any how the efforts made for improving its appearance, could be rejected if it is devoted to a task with too high affective implications.
Abstract: In this paper a neural adaptive control method has
been developed and applied to robot control. Simulation results are
presented to verify the effectiveness of the controller. These results
show that the performance by using this controller is better than
those which just use either direct inverse control or predictive
control. In addition, they show that the resulting is a useful method
which combines the advantages of both direct inverse control and
predictive control.