Abstract: Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.
Abstract: Local obstacle avoidance is critical for mobile robot
navigation. It is a challenging task to ensure path optimality and
safety in cluttered environments. We proposed an Environment
Aware Dynamic Window Approach in this paper to cope with
the issue. The method integrates environment characterization into
Dynamic Window Approach (DWA). Two strategies are proposed
in order to achieve the integration. The local goal strategy guides
the robot to move through openings before approaching the final
goal, which solves the local minima problem in DWA. The adaptive
control strategy endows the robot to adjust its state according
to the environment, which addresses path safety compared with
DWA. Besides, the evaluation shows that the path generated from
the proposed algorithm is safer and smoother compared with
state-of-the-art algorithms.
Abstract: This work addresses the problem of designing an
algorithm capable of generating chaotic trajectories for mobile robots.
Particularly, the chaotic behavior is induced in the linear and angular
velocities of a Khepera III differential mobile robot by infusing them
with the states of the H´enon chaotic map. A possible application,
using the properties of chaotic systems, is patrolling a work area.
In this work, numerical and experimental results are reported and
analyzed. In addition, two quantitative numerical tests are applied in
order to measure how chaotic the generated trajectories really are.
Abstract: The majority of today’s mobile robots are very dependent on battery power. Mobile robots can operate untethered for a number of hours but eventually they will need to recharge their batteries in-order to continue to function. While computer processing and sensors have become cheaper and more powerful each year, battery development has progress very little. They are slow to re-charge, inefficient and lagging behind in the general progression of robotic development we see today. However, batteries are relatively cheap and when fully charged, can supply high power output necessary for operating heavy mobile robots. As there are no cheap alternatives to batteries, we need to find efficient ways to manage the power that batteries provide during their operational lifetime. This paper proposes the use of autonomic principles of self-adaption to address the behavioral changes a battery experiences as it gets older. In life, as we get older, we cannot perform tasks in the same way as we did in our youth; these tasks generally take longer to perform and require more of our energy to complete. Batteries also suffer from a form of degradation. As a battery gets older, it loses the ability to retain the same charge capacity it would have when brand new. This paper investigates how we can adapt the current state of a battery charge and cycle count, to the requirements of a mobile robot to perform its tasks.
Abstract: Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.
Abstract: This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.
Abstract: Assistive robotics are playing a vital role in advancing the quality of life for disable people. There exist wide range of systems that can control and guide autonomous mobile robots. The objective of the control system is to guide an autonomous mobile robot using the movement of eyes by means of EOG signal. The EOG signal is acquired using Ag/AgCl electrodes and this signal is processed by a microcontroller unit to calculate the eye gaze direction. Then according to the guidance control strategy, the control commands of the wheelchair are sent. The classification of different eye movements allows us to generate simple code for controlling the wheelchair. This work was aimed towards developing a usable and low-cost assistive robotic wheel chair system for disabled people. To live more independent life, the system can be used by the handicapped people especially those with only eye-motor coordination.
Abstract: Localization of mobile robots are important tasks for
developing autonomous mobile robots. This paper proposes a method
to estimate positions of a mobile robot using a omnidirectional
camera on the robot. Landmarks for points of references are set
up on a field where the robot works. The omnidirectional camera
which can obtain 360 [deg] around images takes photographs of
these landmarks. The positions of the robots are estimated from
directions of these landmarks that are extracted from the images
by image processing. This method can obtain the robot positions
without accumulative position errors. Accuracy of the estimated
robot positions by the proposed method are evaluated through some
experiments. The results show that it can obtain the positions with
small standard deviations. Therefore the method has possibilities of
more accurate localization by tuning of appropriate offset parameters.
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: In this article we address the problem of mobile robot formation control. Indeed, the most work, in this domain, have studied extensively classical control for keeping a formation of mobile robots. In this work, we design an FLC (Fuzzy logic Controller) controller for separation and bearing control (SBC). Indeed, the leader mobile robot is controlled to follow an arbitrary reference path, and the follower mobile robot use the FSBC (Fuzzy Separation and Bearing Control) to keep constant relative distance and constant angle to the leader robot. The efficiency and simplicity of this control law has been proven by simulation on different situation.
Abstract: In this paper, we study the formation control problem
for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired
formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov
method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations
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: 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: The amplitude response of infrared (IR) sensors
depends on the reflectance properties of the target. Therefore, in
order to use IR sensor for measuring distances accurately, prior
knowledge of the surface must be known. This paper describes the
Phong Illumination Model for determining the properties of a surface
and subsequently calculating the distance to the surface. The angular
position of the IR sensor is computed as normal to the surface for
simplifying the calculation. Ultrasonic (US) sensor can provide the
initial information on distance to obtain the parameters for this
method. In addition, the experimental results obtained by using
LabView are discussed. More care should be taken when placing the
objects from the sensors during acquiring data since the small change
in angle could show very different distance than the actual one.
Since stereo camera vision systems do not perform well under some
environmental conditions such as plain wall, glass surfaces, or poor
lighting conditions, the IR and US sensors can be used additionally to
improve the overall vision systems of mobile robots.
Abstract: In recent years a number of applications with multirobot
systems (MRS) is growing in various areas. But their design
is in practice often difficult and algorithms are proposed for the
theoretical background and do not consider errors and noise in real
conditions, so they are not usable in real environment. These errors
are visible also in task of target localization enough, when robots
try to find and estimate the position of the target by the sensors.
Localization of target is possible also with one robot but as it was
examined target finding and localization with group of mobile robots
can estimate the target position more accurately and faster. The
accuracy of target position estimation is made by cooperation of
MRS and particle filtering. Advantage of usage the MRS with particle
filtering was tested on task of fixed target localization by group of
mobile robots.
Abstract: In this paper, we propose the pre-processor based on
the Evidence Supporting Measure of Similarity (ESMS) filter and also
propose the unified fusion approach (UFA) based on the general
fusion machine coupled with ESMS filter, which improve the
correctness and precision of information fusion in any fields of
application. Here we mainly apply the new approach to Simultaneous
Localization And Mapping (SLAM) of Pioneer II mobile robots. A
simulation experiment was performed, where an autonomous virtual
mobile robot with sonar sensors evolves in a virtual world map with
obstacles. By comparing the result of building map according to the
general fusion machine (here DSmT-based fusing machine and
PCR5-based conflict redistributor considereded) coupling with ESMS
filter and without ESMS filter, it shows the benefit of the selection of
the sources as a prerequisite for improvement of the information
fusion, and also testifies the superiority of the UFA in dealing with
SLAM.
Abstract: Wheeled Mobile Robots (WMRs) are built with their
Wheels- drive machine, Motors. Depend on their desire design of
WMR, Technicians made used of DC Motors for motion control. In
this paper, the author would like to analyze how to choose DC motor
to be balance with their applications of especially for WMR.
Specification of DC Motor that can be used with desire WMR is to
be determined by using MATLAB Simulink model. Therefore, this
paper is mainly focus on software application of MATLAB and
Control Technology. As the driving system of DC motor, a
Peripheral Interface Controller (PIC) based control system is
designed including the assembly software technology and H-bridge
control circuit. This Driving system is used to drive two DC gear
motors which are used to control the motion of WMR. In this
analyzing process, the author mainly focus the drive system on
driving two DC gear motors that will control with Differential Drive
technique to the Wheeled Mobile Robot . For the design analysis of
Motor Driving System, PIC16F84A is used and five inputs of sensors
detected data are tested with five ON/OFF switches. The outputs of
PIC are the commands to drive two DC gear motors, inputs of Hbridge
circuit .In this paper, Control techniques of PIC
microcontroller and H-bridge circuit, Mechanism assignments of
WMR are combined and analyzed by mainly focusing with the
“Modeling and Simulink of DC Motor using MATLAB".
Abstract: A wireless power transfer system can attribute to the
fields in robot, aviation and space in which lightening the weight of
device and improving the movement play an important role. A
wireless power transfer system was investigated to overcome the
inconvenience of using power cable. Especially a wireless power
transfer technology is important element for mobile robots. We
proposed the wireless power transfer system of the half-bridge
resonant converter with the frequency tracking and optimized
power transfer control unit. And the possibility of the application
and development system was verified through the experiment with
LED loads.