A Fuzzy Logic-Based Adaptive Dynamic Window Approach for Path Planning of Automated Driving Mining Truck

Due to COVID-19 pandemic, there is an increasing demand for mobile robots to substitute human in disinfection tasks. New generations of disinfection robots could be developed to navigate in high-risk, high-touch areas. Public spaces, such as airports, schools, malls, hospitals, workplaces and factories could benefit from robotic disinfection in terms of task accuracy, cost, and execution time. The aim of this work is to integrate and analyse the performance of Particle Swarm Optimization (PSO) algorithm, as global path planner, coupled with Dynamic Window Approach (DWA) for reactive collision avoidance using a ROS-based software prototyping tool. This paper introduces our solution – a SLAM (Simultaneous Localization and Mapping) and optimal path planning-based approach for performing autonomous indoor disinfection work. This ROS-based solution could be easily transferred to different hardware platforms to substitute human to conduct disinfection work in different real contaminated environments.

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Event-triggered Model Predictive Adaptive Dynamic Programming for Road Intersection Path Planning of Unmanned Ground Vehicle

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2021.3111692 ◽

2021 ◽

pp. 1-1

Author(s):

Chaofang Hu ◽

Lingxue Zhao ◽

Ge Qu

Keyword(s):

Dynamic Programming ◽

Path Planning ◽

Adaptive Dynamic Programming ◽

Unmanned Ground Vehicle ◽

Ground Vehicle ◽

Adaptive Dynamic ◽

Event Triggered

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Mobile Robot Path Planning Based on Improved Ant Colony Fusion Dynamic Window Approach

10.1109/icma52036.2021.9512795 ◽

2021 ◽

Author(s):

Lei Shao ◽

Qi Li ◽

Chao Li ◽

Wentao Sun

Keyword(s):

Path Planning ◽

Mobile Robot ◽

Ant Colony ◽

Robot Path Planning ◽

Colony Fusion ◽

Window Approach ◽

Robot Path

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Path optimization for navigation of a humanoid robot using hybridized fuzzy-genetic algorithm

International Journal of Intelligent Unmanned Systems ◽

10.1108/ijius-11-2018-0032 ◽

2019 ◽

Vol 7 (3) ◽

pp. 112-119 ◽

Cited By ~ 3

Author(s):

Asita Kumar Rath ◽

Dayal R. Parhi ◽

Harish Chandra Das ◽

Priyadarshi Biplab Kumar ◽

Manoj Kumar Muni ◽

...

Keyword(s):

Genetic Algorithm ◽

Fuzzy Logic ◽

Path Planning ◽

Humanoid Robot ◽

Fuzzy Logic Controller ◽

Target Location ◽

Target Position ◽

Content Type ◽

Hybrid Controller ◽

Fuzzy Genetic

Purpose Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues. Design/methodology/approach Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup. Findings By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors. Originality/value Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.

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