Dynamic path planning of mobile robots with improved genetic algorithm

Mobile robot is an autonomous agent capable of navigating intelligently anywhere using sensor actuator control techniques The applications of the autonomous mobile robot in many fields such as industry space defence and transportation and other social sectors are growing day by day The mobile robot performs many tasks such as rescue operation patrolling disaster relief planetary exploration and material handling etc Therefore an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments Several techniques have been applied by the various researchers for mobile robot navigation and obstacle avoidance The present article focuses on the study of the intelligent navigation techniques which are capable of navigating a mobile robot autonomously in static as well as dynamic environments

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Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

An improved ant colony algorithm is proposed for robot path planning under a static environment.Grid method is used to establish workspace model of the robot.Furthermore,the strategy of backspace from traps and the meeting strategy were applied to path planning of mobile robot,so it avoided path-locked situation as well as improved the efficiency of planning optimal path.The simulation results show that the performance of path planning can be obviously improved by the proposed ant colony algorithm,and the algorithm is very simple and efficient.

An ImproVed Ant Colony Algorithm for Robot Path Planning

An intelligent autonomous robot is required in various applications such as space, transportation, industry, and defense. Mobile robots can also perform several tasks like material handling...

A comprehensive study for robot navigation techniques

It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled. They contain reusable resource that can be recycled and used to generate desired economic benefits. Therefore, performing their efficient disassembly is highly important in green manufacturing and sustainable economic development. Their typical examples are electronic appliances and electromechanical/mechanical products. This paper presents a survey on the state of the art of disassembly sequence planning. It can help new researchers or decision makers to search for the right solution for optimal disassembly planning. It reviews the disassembly theory and methods that are applied for the processing, repair, and maintenance of obsolete/discarded products. This paper discusses the recent progress of disassembly sequencing planning in four major aspects: product disassembly modeling methods, mathematical programming methods, artificial intelligence methods, and uncertainty handling. This survey should stimulate readers to be engaged in the research, development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.

Disassembly Sequence Planning: A Survey

Methodology for Path Planning and Optimization of Mobile Robots: A Review

Time-frequency-based differential scheme is proposed for microgrid protection using non-stationary signal analysis. The non-stationary signal processing algorithm Hilbert-Huang Transform (HHT) have been implemented for the protection objective and the comparative assessment with that of S-transform, differential current is carried out in order to demonstrate the reliability of the proposed protection scheme with different case studies. The series of simulation results demonstrates the efficacy of HHT, than that of S-transform in some critical cases such as high impedance fault where accurate detection is a challenge. The configuration of the microgrid test model has been developed in PSCAD with different distributed generation such as photovoltaic and wind generation system penetrated at different buses. Thus, it is found that the HHT scheme is quite reliable and efficient for fault detection objective.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2015.1563

Microgrid protection using Hilbert–Huang transform based-differential scheme

Path planning strategy for autonomous mobile robot navigation using Petri-GA optimisation

A knowledge based fuzzy-probabilistic roadmap method for mobile robot navigation

In this paper, a Petri-potential-fuzzy hybrid controller (PFHC) for obstacle avoidance and target seeking navigational behaviour of multiple mobile robots in unknown cluttered environments is presented. Based upon a reference motion, direction; distances between the robots and obstacles; distances between the robots and targets are given as inputs to the potential-fuzzy controller. In order to get the requisite information between robots, targets and obstacles each robot is equipped with an array of on board ultrasonic sensors for measuring the distances of obstacles and other robots around it and series of infrared sensors for detecting the bearing of target. To realize the controller in real sense the program is embedded in the robot for online independent navigation. In order to avoid inter robot collision each robot incorporates a set of collision prevention rules implemented as a Petri Net Model in its controller. The resulting navigation algorithm has been implemented on real mobile robots and tested in various environments. Experimental results presented demonstrate the effectiveness and improved performance of the developed controller navigation scheme.

J. C. Mohanta

Papers

Methodology for Path Planning and Optimization of Mobile Robots: A Review

Microgrid protection using Hilbert–Huang transform based-differential scheme

Path planning strategy for autonomous mobile robot navigation using Petri-GA optimisation

A knowledge based fuzzy-probabilistic roadmap method for mobile robot navigation

Navigational control of several mobile robotic agents using Petri-potential-fuzzy hybrid controller