Selected Papers from HNICEM 2007

Author(s):  
Elmer P. Dadios ◽  

The Third International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) was held in Century Park Hotel, Manila, Philippines from March 15 to 18, 2007. The theme on this conference was Technology Creativity and Innovations for Economic Development. As has been done from the previous HNICEM conferences, cutting edge papers presented from this conference are reviewed and selected for JACIII special issue publication. In this special issue, 10 articles are selected that will provide valuable references for researchers and practitioners. The first article presents an integrated algorithm that provides a mobile robot the ability to plan an optimal path and does online collision avoidance in a totally unknown environment. The second article presents a fuzzy controller technique in navigation with obstacle avoidance for a general purpose mobile robot in a given global environment with image processing technique using Open Source Computer Vision. The third article presents a model-based controller for helicopter using the sliding mode approach. The controller assumes that only measured outputs are available and it uses sliding mode observer to estimate the state of the system. The fourth article presents a real-time fuzzy logic based parallel parking system in an FPGA platform. The fifth article presents performance analysis of container unloading operations using simplified analytical model (SAM). The sixth article presents a neuro-fuzzy approach with additional moving average window data filter and fuzzy clustering algorithm use to forecast electrical load. The seventh article presents a new design and implementation of a multi-output fuzzy controller for real time control which utilizes lesser memory and executes faster than an existing type of multiple single-output fuzzy logic controllers. The eight article presents a new method based on multi-objective evolutionary algorithms to evolve low complexity neural controllers that allows an agent to perform two different tasks simultaneously. The ninth and tenth articles present genetic networks programming for stock market trading rules and for traffic systems applications, respectively. We extend our warmest thanks and deepest gratitude to the distinguished authors and reviewers who have contributed to this special issue for their outstanding contributions and cooperation. We are also grateful to Prof. Toshio Fukuda and Prof. Kaoru Hirota, chief editors of JACIII, for their continued support to all the HINICEM International Conferences. Come March 12 to 15, 2009, the 4th HNICEM International Conference will be held in Manila, Philippines. We thank the IEEE Philippines for its continuing sponsorship. Also to JACIII journal, as outstanding papers presented in this conference will be selected for publication in a special issue. We invite you to submit your research papers and to participate in HNICEM 2009. For further information, please visit “http://www.dlsu.edu.ph/conferences/hnicem/”.

Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.


Robotica ◽  
1997 ◽  
Vol 15 (6) ◽  
pp. 627-632 ◽  
Author(s):  
Minglu Zhang ◽  
Shangxian Peng ◽  
Qinghao Meng

This paper is concerned with a mobile robot reactive navigation in an unknown cluttered environment based on neural network and fuzzy logic. Reactive navigation is a mapping between sensory data and commands without planning. This article's task is to provide a steering command letting a mobile robot avoid a collision with obstacles. In this paper, the authors explain how to perform a currently perceptual space partitioning for a mobile robot by the use of an ART neural network, and then, how to build a 3-dimensional fuzzy controller for mobile robot reactive navigation. The results presented, whether experimented or simulation, show that our method is well adapted to this type of problem.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhishek Kumar Kashyap ◽  
Dayal R. Parhi

Purpose This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search algorithm (OSA) and Fuzzy logic. Design/methodology/approach The optimum steering angle (OS) is used to deal with the obstacle located in the workspace, which is the output of the hybrid OSA Fuzzy controller. It is obtained by feeding OSA's output, i.e. intermediate steering angle (IS), in fuzzy logic. It is obtained by supplying the distance of obstacles from all directions and target distance from the robot's present location. Findings The present research is based on the navigation of humanoid NAO in complicated workspaces. Therefore, various simulations are performed in a 3D simulator in different complicated workspaces. The validation of their outcomes is done using the various experiments in similar workspaces using the proposed controller. The comparison between their outcomes demonstrates an acceptable correlation. Ultimately, evaluating the proposed controller with another existing navigation approach indicates a significant improvement in performance. Originality/value A new framework is developed to guide humanoid NAO in complicated workspaces, which is hardly seen in the available literature. Inspection in simulation and experimental workspaces verifies the robustness of the designed navigational controller. Considering minimum error ranges and near collaboration, the findings from both frameworks are evaluated against each other in respect of specified navigational variables. Finally, concerning other present approaches, the designed controller is also examined, and major modifications in efficiency have been reported.


2016 ◽  
pp. 932-954
Author(s):  
Tlijani Hayet ◽  
Tlijani Hatem ◽  
Knani Jilani

This chapter proposes a two-input-and-one-output fuzzy controller for a two-wheeled mobile robot. The robot moves following a hybrid plan based on Genetic Algorithms and Constraint Satisfaction Problem techniques. The path yielded by this hybrid plan is structured by artificial beacons. In each position of these beacons, the current velocity of the controlled robot is by itself an input for the fuzzy controller. The second input is the time delay between the current position and the next sub goal to be reached. The proposed fuzzy controller aims to converge the time delay between positions in the path tracking closely to a time window. It gives the appropriate acceleration so that the time delay becomes closer to the time window.


2020 ◽  
pp. 107488
Author(s):  
Jiling Cao ◽  
Salvador Garcia-Ferreira ◽  
Yasunao Hattori ◽  
Hui Kou ◽  
Sang Youl Lee

2008 ◽  
Vol 41 (2) ◽  
pp. 4393-4399 ◽  
Author(s):  
A. Filipescu ◽  
AL. Stancu ◽  
S. Filipescu ◽  
G. Stamatescu

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Hajer Omrane ◽  
Mohamed Slim Masmoudi ◽  
Mohamed Masmoudi

This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path.


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