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mobile robot navigation using motor schema and fuzzy context dependent behavior modulation

APPLIED SOFT COMPUTING 2008年第1期8卷 422-436页

作者： Huq, Rajibul Mann, George K. I. Gosine, Raymond G. Mem Univ Newfoundland Fac Engn C CORE St John NF Canada

This paper presents a novel technique to autonomously select different motor schemas using fuzzy context dependant blending of robot behaviors for navigation. First, a set of motor schemas is formed as behaviors. Both strategic and reactive type schemas have been employed in order to facilitate both the aspects of global and local motion planning. While strategic schemas are formed using the prior knowledge of the environment, the reactive schemas are activated using current sensory data of the robot. For global path planning, a safe path is first created using a Voronoi diagram. For local planning, the Voronoi vertices are treated as immediate subgoals and are used to form schemas leading to achieve optimized traveled distance and goal oriented robot navigation. Two motor schemas are formed as reactive behaviors for obstacle avoidance. The unknown obstacles are modeled using the sensory data. The coordinated behavior is achieved while employing weighed vector summation of the schemas. The adaptation of weights are achieved through a fuzzy inference system where fuzzy rules are used to dynamically generate the weights during navigation. A novel approach is proposed for fuzzy context-dependent blending of schemas. Fuzzy rules are formed using two main criteria into account: the first criterion reasons out the context dependent activity of a schema for achieving goal and the second criterion reasons out cooperative activity of strategic schemas with high priority reactive schemas. Comprehensive results validate that the proposed technique eliminates the existing drawbacks of motor schema approaches available in literature and provides collision free goal oriented robot navigation. (C) 2007 Elsevier B. V. All rights reserved.

关键词： mobile robot navigation global and local motion planning motor schema Voronoi diagram fuzzy context dependent blending behavior modulation

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mobile robot navigation for complete coverage of an environment

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IFAC-PapersOnLine 2018年第22期51卷 512-517页

作者： Šelek, Ana Seder, Marija Petrovi, Ivan Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Croatia

Inspired by the Spanning Tree Covering (STC) algorithm of Gabriely and Rimon, a novel algorithm of complete coverage for known environments is developed. Unlike the original STC algorithm, we detect dynamic elements of the environment and efficiently update the solution when changes are observed. The contribution is a path replanning algorithm that reduces overlapping when the part of the environment is changed. Experiments show that the proposed algorithm is capable of planning complete coverage robot paths with 70.27% coverage and without overlapping. © 2018

关键词： mobile robots Collision avoidance Motion planning robot programming Trees (mathematics) Complete coverages Dynamic elements Known environments mobile robot navigation Novel algorithm Path re planning robot path Spanning tree

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mobile robot navigation with the combination of supervised learning in cerebellum and reward-based learning in basal ganglia

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COGNITIVE SYSTEMS RESEARCH 2020年 59卷 1-14页

作者： Wang, Dongshu Hu, Yuhang Ma, Tianlei Zhengzhou Univ Sch Elect Engn Zhengzhou 450001 Henan Peoples R China

Autonomous navigation of mobile robot in unknown environment has attracted much attention of scholars over the past decades, and many bio-inspired heuristic navigation models have been presented, such as the cerebellum and basal ganglia models. Pervious cerebellum and basal ganglia model, however, treats them as parallel and independent system, without interaction between them, or combines their function together, but with only unidirectional communication between them. Based on the cognition and developmental mechanism of the biology, this paper proposes a novel navigation model, which uses the motivated developmental network (MDN) to mimic the supervised learning of the cerebellum and the reinforcement learning based on the radial basis function neural network (RBFNN) to simulate the reward-based learning of the basal ganglia, and integrates them together to construct a hybrid complex cognition model, to navigate a mobile robot in unknown environment. During the environment exploration, for the unexplored places, the artificial agent uses the cerebellum model to choose action, instead of the epsilon-greedy method, to accelerate the learning convergence speed of the basal ganglia. For the explored places, it directly uses the basal ganglia based on the RBFNN to explore, then update and perfect the knowledge base of the cerebellum, which enable the cerebellum to achieve better decision in the following exploration. Hence, it realizes not only the two way communication between the cerebellum and basal ganglia, but also the co-development of them. Experimental results show that this model can enable the agent to autonomously development its intelligence through the hybrid learning. As far as we know, this is the first work to realize the direct communication between the basal ganglia and the cerebellum. (C) 2019 Elsevier B.V. All rights reserved.

关键词： mobile robot navigation Basal ganglia Cerebellum Developmental network Supervise learning Reinforcement learning

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mobile robot navigation in Cluttered Environment Using Spider Monkey Optimization Algorithm

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING 2020年第4期44卷 1673-1685页

作者： Singh, Ngangbam Herojit Thongam, Khelchandra Natl Inst Technol Mizoram Aizawl India Natl Inst Technol Manipur Imphal Manipur India

Swarm intelligence is one of the most emerging methods used for autonomous mobile robot navigation. Researchers have developed many algorithms in mobile robot navigation by simulating the swarming behavior of various creatures like ants, firefly, honey bees, and cuckoo, and the findings are very motivating. The paper presents application and implementation of spider monkey optimization (SMO) along with Three Path method (TPM) for mobile robot navigation in cluttered environment. A collision-free path is selected by using TPM. When all the three paths are blocked by obstacles, SMO is used for obstacles avoidance. The finding of global and local leaders from the groups is the key concept of the proposed method. The proposed method efficiently improves the global search in less number of iterations, and hence, it can be easily implemented for real-time obstacle avoidance. The computational path and time are less as compared to other navigational methods. Some simulation results are presented at the end of the paper to show the effectiveness of the proposed navigational method.

关键词： Swarm intelligence Spider monkey optimization mobile robot navigation Obstacle avoidance

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mobile robot navigation by a distributed vision system

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NEW GENERATION COMPUTING 2001年第2期19卷 121-137页

作者： Sogo, T Ishiguro, H Ishida, T Kyoto Univ Dept Social Informat Sakyo Ku Kyoto 6068501 Japan Wakayama Univ Dept Comp & Commun Sci Wakayama 6408510 Japan

This paper proposes a Distributed Vision System (DVS), which is an intelligent infrastructure for mobile robots consisting of many vision agents (VAs) embedded in an environment. The system monitors the environment from various viewing points with the VAs, maintains the dynamic environment models, and provides various information to robots. Based on this concept, we have developed a prototype of the DVS which consists of sixteen vision agents and simultaneously navigates two robots in a model town.

关键词： distributed vision system vision agents mobile robot navigation perceptual information infrastructure

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mobile robot navigation Under Pose Uncertainty in Unknown Environments

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IFAC-PapersOnLine 2017年第1期50卷 12710-12714页

作者： Arvanitakis, Ioannis Tzes, Anthony Giannousakis, Konstantinos Department of Electrical & Computer Engineering University of Patras Rio26500 Greece Electrical & Computer Engineering Program New York University Abu Dhabi Abu Dhabi United Arab Emirates

The navigation of a mobile robot under uncertainty in its pose information in an unknown environment is the subject of this paper. The mobile robot is equipped with a limited-field of view limited-range finder and a magnetometer to infer its orientation. The target location is known, while the robot's localization suffers from measurement errors. The uncertainty is taken into consideration by calculation of the Guaranteed Visibility and Guaranteed Sensed Area, where safe navigation can be assumed regardless of the measurement error. A switching objective function initially guarantees the exploration towards the target area and afterwards safely guides the robot towards it. Simulation results that prove the efficiency of the proposed scheme are presented. © 2017

关键词： mobile robots Control engineering Intelligent robots Measurement errors navigation Range finders robotics Uncertainty analysis Autonomous robotic systems Intelligent robotics mobile robot navigation Objective functions Pose information Pose sensing Safe navigations Unknown environments

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mobile robot navigation using Alpha Level Fuzzy Logic System: Experimental Investigations

Mobile Robot Navigation using Alpha Level Fuzzy Logic System...

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IEEE International Conference on System, Man, and Cybernetic

作者： Parasuraman, S. Ganapathy, V. Shirinzadeh, Bijan Monash Univ Sch Engn Bandar Sunway 46150 Malaysia Monash Univ Dept Engn Mech Clayton Vic 3800 Australia

ISBN: (纸本)9781424423835

This paper presents the issues associated with the mobile robot navigation and the establishment of a new technique to navigate the mobile robot in a real world environment. The issues discussed are (i) If multiple obstacles are appeared in the environment with equal distances as perceived from multiple sensors of robot, then the corresponding multiple obstacles are treated as a whole and the robot deviate from obstacles widely and avoid then reaching to the target. As a result of the wide deviation, the robot takes long time and long path to reach the target position. (ii) Behavior rule selection when multiple obstacles are appeared in the environment with equal distances from robot. The robot navigation with optimal path, time and rule selection are more important and critical task, whenever the mobile robots are engaged to search the lives in the event of natural disaster like earthquake etc. A new methodology is proposed and used for resolving the above issues and discussed in this paper. The mathematical aspect of resolving conflicts is presented the following section.

关键词： mobile robot navigation Fuzzy logic system Behavior selection Behavior Conflicts

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mobile robot navigation Using Circular Path Planning Algorithm

Mobile Robot Navigation Using Circular Path Planning Algorit...

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International Conference on Control, Automation and Systems

作者： Han, Sung-Min Lee, Kang-Woong Korea Aerosp Univ Sch Elect Telecommun & Comp Engn Seoul South Korea

ISBN: (纸本)9788995003893

In this paper we propose a circular path planning algorithm for a mobile robot using only monocular vision system. The proposed method reduces the size of image data obtained by CCD camera to improve the image processing speed and noise immunity. A circular path for obstacle avoidance of the mobile robot is determined by the position and size of obstacles. Velocity of the mobile robot is controlled to guarantee stable movement. We show performance of the proposed method through experiments on Pioneer2-DX.

关键词： mobile robot navigation obstacle avoidance vision system circular path planning

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mobile robot navigation using RFID and vision sensor

Mobile robot navigation using RFID and vision sensor

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International Symposium on Information Technology Convergence

作者： Chae, Heesung Na, Sangik Elect & Telecommun Res Inst Intelligent Robot Res Div Taejon 305606 South Korea

ISBN: (纸本)9780769530451

This paper illustrate an efficient method for global localization incorporating signal detection from artificial landmark consisted of RFID tags, and for fine localization incorporating feature descriptor derived from a view of scene. The system incorporates a RFID reader on a mobile robot checking the signal from RFID tags to localize the robot with respect to global position. After determining the global position of the robot, the feature matching can be used to checking the local position of it in a predetermined global position. And we propose a successive global-to-fine localization algorithm using RFID tags and feature matching respectively. The experimental results showed the proposed algorithm has improved the localization performance on indoor environments with a mobile robot.

关键词： mobile robot navigation RFID tags vision sensors mobile robots RFID reader robot indoor environment signal acquisition

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mobile robot navigation for Human-robot Social Interaction 16

Mobile Robot Navigation for Human-Robot Social Interaction

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16th International Conference on Control, Automation and Systems (ICCAS)

作者： Patompak, Pakpoom Jeong, Sungmoon Chong, Nak Young Nilkhamhang, Itthisek Japan Adv Inst Sci & Technol Sch Informat Sci 1-1 Asahidai Nomi Ishikawa 9231292 Japan Thammasat Univ Sirindhorn Int Inst Technol Sch Informat Comp & Commun Technol 99 Khlong Luang Pathum Thani 12120 Thailand

ISBN: (纸本)9788993215120

Human social interactions are believed to be described by a mathematical model called the Social Force Model (SFM). A variety of mobile robot research has often used the SFM to generate an appropriate navigation behavior. However, to create a mobile robot that moves around in a human-populated environment in a socially acceptable way, it should be stressed that the social conventions are strictly obeyed. This paper proposes an extended SFM between humans and robots, called the Social Relationship Model (SRM), to enable mobile robots to generate navigation paths in a human-like manner. Simulation results show notable advantages of SRM over the Transition based Rapidly Random Tree (T-RRT) path planning algorithm. The proposed method ensures a socially acceptable robot path, one of the most important issues for human-robot symbiosis.

关键词： mobile robot navigation Social Force Model Social Relationship Model Human-robot Symbiosis

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