scholarly journals Prototyping Non-holonomic Hovercraft for Path Planning and Obstacle Avoidance

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ghulam -e-Mustafa Abro ◽  
Zain Anwar Ali ◽  
Bazgha Jabeen
Keyword(s):  
Path Planning ◽  
Control Systems ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Digital Image ◽  
Pid Control ◽  
Control Algorithm ◽  
Autonomous Control ◽  
Physical Quantities

— By definition, autonomous control systems are thesystems that sense the physical quantities from their environmentand may execute any dirty, difficult, dull and dangerous taskwithout any intervention. These systems are mostly used in thetransportation of large packages from one place to anotherautonomously by selecting the shortest path, accurate speed andobstacle avoidance. This paper describes the development offuzzy based PID control algorithm to tackle the dynamicconstraints of localization for proposed non-holonomichovercraft. Furthermore, in order to monitor the hovercraft thatwhether it is hovering in a familiar or strange environment;paper suggests the incorporation of digital image processingtechnique which will regularly correlate, the images beingcaptured by the prototype. Moreover, paper methodology alsoprovides the deployment way along with the interfacingtechniques of some configurable sensors, which will share theinformation related to the surroundings of hovercraft usinginternet of things (IoT).

scholarly journals Prototyping Non-holonomic Hovercraft for Path Planning and Obstacle Avoidance

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Ghulam -e-Mustafa Abro ◽  
Zain Anwar Ali ◽  
Bazgha Jabeen
Keyword(s):  
Path Planning ◽  
Control Systems ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Digital Image ◽  
Pid Control ◽  
Control Algorithm ◽  
Autonomous Control ◽  
Physical Quantities

— By definition, autonomous control systems are thesystems that sense the physical quantities from their environmentand may execute any dirty, difficult, dull and dangerous taskwithout any intervention. These systems are mostly used in thetransportation of large packages from one place to anotherautonomously by selecting the shortest path, accurate speed andobstacle avoidance. This paper describes the development offuzzy based PID control algorithm to tackle the dynamicconstraints of localization for proposed non-holonomichovercraft. Furthermore, in order to monitor the hovercraft thatwhether it is hovering in a familiar or strange environment;paper suggests the incorporation of digital image processingtechnique which will regularly correlate, the images beingcaptured by the prototype. Moreover, paper methodology alsoprovides the deployment way along with the interfacingtechniques of some configurable sensors, which will share theinformation related to the surroundings of hovercraft usinginternet of things (IoT).

Space robot motion path planning based on fuzzy control algorithm

2021 ◽  
pp. 1-8
Author(s):  
Baoyu Shi ◽  
Hongtao Wu
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Space Robot ◽  
Robot Motion ◽  
Robot Path Planning ◽  
Behavior Based ◽  
Fuzzy Control Algorithm ◽  
Robot Path

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

Processor Performance Required for Decentralized Kinematic Control Algorithm of Module-Type Hyper-Redundant Manipulator

1996 ◽  
Vol 8 (5) ◽  
pp. 442-446 ◽  
Author(s):  
Shinichi Kimura ◽  
◽  
Toshiyuki Okuyama
Keyword(s):  
Control Systems ◽  
Local Control ◽  
Control Algorithm ◽  
Autonomous Systems ◽  
Careful Consideration ◽  
Autonomous Control ◽  
Redundant Manipulators ◽  
Processor Performance ◽  
Microgravity Conditions ◽  
Module Type

Based on the great progress of studies on decentralized autonomous systems, the decentralized autonomous control mechanism has expand its territory of applications to the control of redundant manipulators. Because local control systems are closely related in the decentralized autonomous control of redundant manipulators, the performance of local control systems requires careful consideration, particularly in treating the dynamic aspects of manipulators. In this paper, computer simulation is used to assess the effects of the processor performance of a decentralized autonomous control algorithm in adaptation to the reactive motion caused by the failure of actuators under microgravity conditions. The results show that the algorithm is so simple that conservative 16-bit processors are feasible as the local processor of the decentralized autonomous control algorithm. These results suggest that the decentralized autonomous control algorithm may have great advantages in hardware architecture cost and resources. The effect of conflicts among local processors on system performance is also discussed.

PID Temperature Control Systems of Greenhouse Based on FSM Methodology

2015 ◽  
Vol 740 ◽  
pp. 225-228
Author(s):  
Yang Liu ◽  
Ji Qian ◽  
Juan Zhou
Keyword(s):  
Control Systems ◽  
Temperature Control ◽  
Pid Control ◽  
Control Algorithm ◽  
High Reliability ◽  
Variable Temperature ◽  
Good Control ◽  
Control Effect ◽  
Finite State ◽  
Reduced Instruction Set Computer

PID Temperature Control Systems of Greenhouse Based on FSM (finite state machines) Methodology is used in variable-temperature-controlled greenhouse. This system cored with an advanced 16 bit RISC (Reduced Instruction Set Computer) MPU MSP430F149 with low power. The sensors employ a higher accuracy Pt1000 Resistance Temperature sensor and Silicon Photoelectric Generator. In software design, it used the thinking of FSM programming increment style PID Control algorithm. The Flexible Application of FSM can make the program clear and more effectively to management. The increment style PID Control algorithm avoids paranormal value when setting temperature is changed and temperature control more accurately. The cite operation shows that this controller has the advantages such as high reliability and good control effect.

scholarly journals Combining turning point detection and Dijkstra’s algorithm to search the shortest path

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401668335 ◽  
Author(s):  
Ter-Feng Wu ◽  
Pu-Sheng Tsai ◽  
Nien-Tsu Hu ◽  
Jen-Yang Chen
Keyword(s):  
Image Processing ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Turning Point ◽  
Dijkstra’S Algorithm ◽  
Edge Point ◽  
Dijkstra's Algorithm ◽  
Before And After ◽  
Point Detection

In this study, image processing was combined with path-planning object-avoidance technology to determine the shortest path to the destination. The content of this article comprises two parts: in the first part, image processing was used to establish a model of obstacle distribution in the environment, and boundary sequence permutation method was used to conduct orderly arrangement of edge point coordinates of all objects, to determine linking relationship between each edge point, and to individually classify objects in the image. Then, turning point detection method was used to compare the angle size between vectors before and after each edge point and to determine vertex coordinates of polygonal obstacles. In the second part, a modified Dijkstra’s algorithm was used to turn vertices of convex-shaped obstacles into network nodes, to determine the shortest path by a cost function, and to find an obstacle avoidance path connecting the start and end points. In order to verify the feasibility of the proposed architecture, an obstacle avoidance path simulation was made by the graphical user interface of the programming language MATLAB. The results show that the proposed method in path planning not only is feasible but can also obtain good results.

scholarly journals IMPROVEMENT OF CONTROL ALGORITHM FOR MOBILE ROBOT USING MULTI-LAYER SENSOR FUSION

2021 ◽  
Vol 59 (1) ◽  
pp. 110
Author(s):  
Ha Xuan Nguyen ◽  
Huy Van Nguyen ◽  
Tung Thanh Ngo ◽  
Anh Duy Nguyen
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Sensor Fusion ◽  
Control Algorithm ◽  
Experimental Implementation ◽  
Different Shapes ◽  
High Repeatability ◽  
Very High

Mobile robots have received much of attention in the last three decades due to their very high potential of applications such as smart logistics, exploration, and intelligent services. One of important functions of mobile robots is the navigation in which robot must know their location, the maps of environment and perform path planning with obstacle avoidance. In this work, we introduce an improvement of control algorithm for mobile robot using multi-layer sensor fusion toward the target of efficient obstacle avoidance. Based on our method, we used three layers of sensors arranging in three height-different planes of robot’s housing for sensor fusion. A control algorithm, which is extended from the so-called bubble rebound algorithm and uses signal from sensor system, was proposed. Experimental implementation on a mobile robot, named EAI, shows that our algorithm can control the robot to navigate and avoid obstacles much efficiently, in which obstacles in forms of different shapes and height can also be avoided. A high repeatability and stability of the algorithm is obtained.

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