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Recognising plants with ultrasonic sensing for mobile robot navigation

robotICS AND AUTONOMOUS SYSTEMS 2001年第2-3期34卷 71-82页

作者： Harper, N McKerrow, P Univ Wollongong Sch Informat Technol & Comp Sci Wollongong NSW 2522 Australia

mobile robots navigate through many environments that contain plants. A sensor that can recognise plants would be useful for navigation in these environments. Two problems make plant sensing difficult: plant similarity and plant asymmetry with rotation. a continuously transmitted frequency modulated ultrasonic sensor produces a return signal that contains information about the geometric structure: of plants. Correlation of echoes from many orientations show that plants can be recognised with sufficient accuracy for navigation. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： CTFM ultrasonics mobile robot navigation

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Using real-time stereo vision for mobile robot navigation

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AUTONOMOUS robotS 2000年第2期8卷 161-171页

作者： Murray, D Little, JJ Univ British Columbia Dept Comp Sci Vancouver BC V5Z 1M9 Canada

This paper describes a working vision-based mobile robot that navigates and autonomously explores its environment while building occupancy grid maps of the environment. We present a method for reducing stereo vision disparity images to two-dimensional map information. Stereo vision has several attributes that set it apart from other sensors more commonly used for occupancy grid mapping. We discuss these attributes, the errors that some of them create, and how to overcome them. We reduce errors by segmenting disparity images based on continuous disparity surfaces to reject "spikes" caused by stereo mismatches. Stereo vision processing and map updates are done at 5 Hz and the robot moves at speeds of 300 cm/s.

关键词： stereo vision mobile robot navigation

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Neurofuzzy-based approach to mobile robot navigation in unknown environments

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS 2007年第4期37卷 610-621页

作者： Zhu, Anmin Yang, Simon X. Shenzhen Univ Coll Informat Engn Shenzhen 518060 Peoples R China Univ Guelph Sch Engn ARIS Lab Guelph ON N1G 2W1 Canada

In this paper, a neurofuzzy-based approach is proposed, which coordinates the sensor information and robot motion together. A fuzzy logic system is designed with two basic behaviors, target seeking and obstacle avoidance. A learning algorithm based on neural network techniques is developed to tune the parameters of membership functions, which smooths the trajectory generated by the fuzzy logic system. Another learning algorithm is developed to suppress redundant rules in the designed rule base. A state memory strategy is proposed for resolving the "dead cycle" problem. Under the control of the proposed model, a mobile robot can adequately sense the environment around, autonomously avoid static and moving obstacles, and generate reasonable trajectories toward the target in various situations without suffering from the "dead cycle" problems. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies.

关键词： "dead cycle" problem mobile robot navigation neurofuzzy parameter tuning redundant rule suppression

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An integrated learning approach to environment modelling in mobile robot navigation

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NEUROCOMPUTING 2004年第1-4期57卷 215-238页

作者： Ster, B Univ Ljubljana Fac Comp & Informat Sci Ljubljana 1001 Slovenia

We extend the approach to learning a topological description of the environment with recurrent neural networks. Usually, a predetermined reactive behavior and a predefined criterion for decision points are used. In our extended approach, both the reactive behavior and the criterion for the decision points are adaptive and therefore more flexible. The reactive behavior is learnt using reinforcement learning supplemented by a new, psychologically grounded mechanism that enables the robot to autonomously explore the environment in a useful way for the purposes of modelling. Decision points or situations where a deviation from the reactive behavior is allowed are learnt on-line using a novel criterion based on the information theory. Results of experiments conducted with a simulated mobile robot equipped with proximity sensors and a color video camera show applicability of the proposed approach. (C) 2003 Elsevier B.V. All rights reserved.

关键词： recurrent neural networks mobile robot navigation reinforcement learning

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Contour tracking of an unknown planar object by regulating force for mobile robot navigation

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robotICA 2007年第3期25卷 297-305页

作者： Jung, Seul Jeon, Poongwoo Hsia, T. C. Chungnam Natl Univ Intelligent Syst & Emot Engn Lab Mechatron Grp BK21 Taejon 305764 South Korea Univ Calif Davis Dept Elect & Comp Engn Davis CA 95616 USA

In this paper, a novel contour-tracking control method of an unknown planar object by lateral force regulation for wheeled mobile robot navigation is presented. The robot is required to follow the contour of an unknown object toward the goal position. Based on mobile robot dynamic equations, a force-control algorithm is proposed to maintain constant contact with a planar object. Measured contact force from an object is used not only to regulate a contact force in a lateral direction, but also to control the orientation angle of the robot to avoid collision with an object. Simulation and experiment of contour-tracking tasks of a wheeled mobile robot are conducted. Experimental results show that the contact force is well-regulated, and the robot arrives at the goal position successfully.

关键词： contour tracking mobile robot navigation force control

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Human-Observation-Based Extraction of Path Patterns for mobile robot navigation

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2010年第4期57卷 1401-1410页

作者： Sasaki, Takeshi Brscic, Drazen Hashimoto, Hideki Univ Tokyo Inst Ind Sci Tokyo 1538505 Japan Tech Univ Munich Inst Automat Control Engn D-80290 Munich Germany

In this paper, a mobile robot navigation method based on the observation of human walking is presented. The proposed method extracts paths that are frequently used by human and builds a topological map of the environment from the observed human walking paths. Unlike the conventional methods, the proposed method enables us to generate paths which are practical, have no obstacles, and are natural for humans since the paths reflect the motion of persons. For realizing the human observation in a large area, in this paper, multiple vision sensors are placed in space. By using distributed sensors, people can be observed even when the robot is not near them or if they are hidden behind obstacles. mobile robot navigation based on the topological map is also performed with the support of the distributed sensors. The global position of the mobile robot can be directly measured by using external sensors, which makes the localization problem much easier. Based on the position information, the mobile robot can follow the generated paths and reach the goal point while avoiding obstacles.

关键词： Human observation intelligent space (iSpace) mobile robot navigation

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Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

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robotICS AND AUTONOMOUS SYSTEMS 2008年第3期56卷 247-264页

作者： Nunez, P. Vazquez-Martin, R. del Toro, J. C. Bandera, A. Sandoval, F. Univ Malaga ETSI Telecomunicac Dpto Tecnol Elect Grp Ingn Sist Integrados E-29071 Malaga Spain

This paper proposes a geometrical feature detection system which is to be used with conventional 2D laser range finders. It consists of three main modules: data acquisition and pre-processing, segmentation and landmark extraction and characterisation. The novelty of this system is a new approach for laser data segmentation based on an adaptive curvature estimation. Contrary to other works, this approach divides the laser scan into line and curve segments. Then, these items are used to directly extract several types of landmarks associated with real and virtual features of the environment (corners, center of tree-like objects, line segments and edges). For each landmark, characterisation provides not only the parameter vector, but also complete statistical information, suitable to be used in a localization and mapping algorithm. Experimental results show that the proposed approach is efficient to detect landmarks for structured and semi-structured environments. (c) 2007 Elsevier B.V. All rights reserved.

关键词： natural landmark extraction mobile robot navigation adaptive curvature estimation covariance matrix

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MoDeT: a low-cost obstacle tracker for self-driving mobile robot navigation using 2D-laser scan

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INDUSTRIAL robot-THE INTERNATIONAL JOURNAL OF robotICS RESEARCH AND APPLICATION 2022年第6期49卷 1032-1041页

作者： Nguyen, Toan Van Do, Minh Hoang Jo, Jaewon Seoul Natl Univ Sci & Technol Dept Elect & Informat Engn Seoul South Korea Syscon Robot R&D Ctr Incheon South Korea

Purpose Collision avoidance is considered as a crucial issue in mobile robotic navigation to guarantee the safety of robots as well as working surroundings, especially for humans. Therefore, the position and velocity of obstacles appearing in the working space of the self-driving mobile robot should be observed to help the robot predict the collision and choose traversable directions. This paper aims to propose a new approach for obstacle tracking, dubbed MoDeT. Design/methodology/approach First, all long lines, such as walls, are extracted from the 2D-laser scan and considered as static obstacles (or mapped obstacles). Second, a density-based procedure is implemented to cluster nonwall obstacles. These clusters are then geometrically fitted as ellipses. Finally, the combination of Kalman filter and global nearest-neighbor (GNN) method is used to track obstacles' position and velocity. Findings The proposed method (MoDeT) is experimentally verified by using an autonomous mobile robot (AMR) named AMR SR300. The MoDeT is found to provide better performance in comparison with previous methods for self-driving mobile robots. Research limitations/implications The robot can only see a part of the object, depending on the light detection and ranging scan view. As a consequence, geometrical features of the obstacle are sometimes changed, especially when the robot is moving fast. Practical implications This proposed method is to serve the navigation and path planning for the AMR. Originality/value (a) Proposing an extended weighted line extractor, (b) proposing a density-based obstacle detection and (c) implementing a combination of methods [in (a) and (b) constant acceleration Kalman and GNN] to obtain obstacles' properties.

关键词： mobile robots Autonomous robots Collision avoidance mobile robot navigation Density-based clustering 2D-laser obstacle tracker

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Z-Number-Based Fuzzy Logic Approach for mobile robot navigation

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IEEE ACCESS 2023年 11卷 131979-131997页

作者： Khan, Osama Ali Kunwar, Faraz Khan, Umar Shahbaz Jabbar, Hamid Natl Univ Sci & Technol NUST Islamabad 44000 Pakistan Natl Univ Sci & Technol NUST Coll Elect & Mech Engn Dept Mechatron Engn Rawalpindi 04623 Pakistan

The primary objective of this study is to investigate the effects of mobile robot navigation using a fuzzy logic framework based on Z-numbers implemented within the robot Operating System (ROS) Noetic. The methodology addresses uncertainty and imprecise information in robot navigation using extensive simulations performed using the TurtleBot3 robot in the ROS framework. Our unique approach enables the autonomous navigation of mobile robots in unknown environments, utilizing fuzzy rules with multiple inputs and outputs. The navigation strategy relies on the laser scan sensor, the Adaptive Monte Carlo Localization (AMCL) algorithm, and particle filter mapping, enabling real-time localization and mapping capabilities. Path planning incorporates local and global planners, while obstacle avoidance generates collision-free paths by dynamically detecting and circumventing obstacles in the robot's proximity. We employ Simultaneous Localization and Mapping (SLAM) techniques to estimate the robot's position and create a map of the environment. Our integration of these methods presents a promising solution for autonomous mobile robot navigation in real-world applications, thereby advancing the capabilities of robot systems in complex environments. Our results demonstrate the suitability and effectiveness of using a Z-number-based system in the navigation scenarios of mobile robots.

关键词： Z-number fuzzy logic mobile robot navigation path planning obstacles avoidance simultaneous localization and mapping (SLAM)

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Integration of reactive behaviors and enhanced topological map for robust mobile robot navigation

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 1999年第5期29卷 474-485页

作者： Ryu, BS Yang, HS Korea Adv Inst Sci & Technol Ctr Artificial Intellegence Res Dept Comp Sci Taejon 305701 South Korea

A navigation system for an autonomous mobile robot working in indoor environments is presented. The system takes advantage of deliberative (plan-based) approach and reactive (behavior-based) approach. In the reactive part of the system are local behaviors that are independent, action-generating entities. We also provide higher-level deliberative modules that make interactions manageable so the system can accomplish more meaningful tasks. The deliberative modules control the activation and deactivation of individual local behaviors based on current situations, representing the position of the robot and the path to the goal. The situation is determined by a mapping subsystem consisting of an enhanced topological map, a localization module and a planning module. The use of the explicit world model, especially in a topological manner, makes it possible to reliably localize the robot and plan an efficient path. This paper also provides a detailed description of a localization module based on dead reckoning, and a planning module that selects an efficient and reliable path.

关键词： enhanced topological map mobile robot navigation reactive behavior

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