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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
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A novel navigation algorithm for collaborative multi robots
Published 2010“…Some research papers based on collaborative robots have been reviewed in this paper; from review analysis we have developed an algorithm with behavioral based distributed knowledge of multi-agents for accomplishing collaborative navigation. …”
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IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…Behaviour-based architecture is one of the most effective autonomous navigation techniques, second only to machine learning. …”
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Final Year Project -
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A collaborative navigation algorithm for multi-agent robots in autonomous reconnaissance mission
Published 2010“…Some research papers based on collaborative robots have been reviewed in this paper; from review analysis we have developed an algorithm with behavioral based distributed knowledge of multi-agents for accomplishing collaborative navigation. …”
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Proceeding Paper -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms
Published 2024“…In these quick analyses, we pull out the most important concepts, article types, rating criteria, and the positives and negatives of each piece. Based on the findings of this review, we can conclude that an efficient solution for indoor navigation that uses the capabilities of embedded data and technological advances in immersive technologies can be achieved by training the shortest path algorithm with a deep learning algorithm to enhance the indoor navigation system.…”
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Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments
Published 2017“…Simulation in dynamic environment is used to evaluate the performance of collision prediction based GNP-RL compared with that of two state-of-the art navigation approaches, namely, Q-Learning (QL) and Artificial Potential Field (APF). …”
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Conference or Workshop Item -
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Advancing mobile robot navigation with DRL and heuristic rewards: a comprehensive review
Published 2025“…The advent of Deep Reinforcement Learning (DRL) has spurred significant research into enabling mobile robots to learn effective navigation by optimizing actions based on environmental rewards. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm
Published 2012“…Algorithm for straight-line correction was based on PI(D) controller. …”
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Citation Index Journal -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot
Published 2023“…Autonomous mobile robot path planning in unknown and dynamic environment is a crucial task for successful mobile robot navigation. This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot
Published 2023“…Autonomous mobile robot path planning in unknown and dynamic environment is a crucial task for successful mobile robot navigation. This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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Testing the minimal bounded space method on vision-based drone navigation / Yap Seng Kuang
Published 2021“…Recently, the availability of the deep learning algorithm also encourages the object-based approach for drone navigation. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot
Published 2023“…Autonomous mobile robot path planning in unknown and dynamic environment is a crucial task for successful mobile robot navigation. This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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