Landmark manipulation system for mobile robot navigation
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Abstract:
In mobile robot scenarios, it is expected that the robot autonomously navigates through home or office environments and processes objects/landmarks during navigation. Landmark manipulation is identified as one important research area in robot navigation systems. We have developed an online robot landmark processing system (RLPS) to detect, classify, and localize different types of landmarks during robot navigation. The RLPS is based on a two-step classification stage which is robust and invariant towards scaling and translations. It provides a good balance between fast processing time and high detection accuracy by combining the strengths of appearance-based and model-based object classification techniques. The experimental results showed that the RLPS is more powerful as it recognizes a wide range of landmarks and efficiently handles landmarks with occlusions, viewpoint variances, and illumination changes.Keywords:
Landmark
Mobile Robot Navigation
Navigation System
A navigation system is a program that provides graphical maps, co-ordinates or directions to a destination. Now autonomous navigation system of a mobile robot involves self-steering of a robot from one place to another based on computational resources on-board the robot. There are several ways to approach mobile robot navigation. This paper discusses the most common algorithms used for any kind of mobile robots for navigational purpose which are go-to-goal, avoiding obstacles, following wall and path planning. Sonar range sensors are used as the sensing elements and wheel encoders are used for robot localization. Simulation results are presented to verify the effectiveness of the proposed navigation system in an unknown environment which contain convex and concave objects. To test the proposed algorithms in real life, a differential drive wheeled robot which is a kind of mobile robot, has been made. However, this paper also contains the motor model of differential drive wheeled robot.
Mobile Robot Navigation
Navigation System
Personal robot
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Current in vehicle navigation systems place an emphasis on the use of distances within their turn-by-turn directions. Previous work has shown the potential for landmarks, particularly in relation to subjective aspects of system usability e.g. confidence in navigation. To test the objective benefits of landmarks versus distances, road based trials were conducted in which 28 participants drove unfamiliar routes within an urban area using a simulated navigation system that emphasizes either landmarks or distances for the purposes of locating maneuvers. When using the landmark system, relatively few glances were made towards the navigation display and workload was perceived to be lower, in comparison with the figures attained for the distance system. Furthermore, the duration of glances towards the landmark display was low. Nevertheless, the participants made some navigational errors when using landmarks. The results are discussed in relation to the design of future landmark-oriented navigation systems.
Landmark
Turn-by-turn navigation
Navigation System
Interface (matter)
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Self-localisation is an essential competence for mobile robot navigation. Due to the fundamental unreliability of dead reckoning, a robot must depend on its perception of external environmental features or landmarks to localise itself. A key question is how to evaluate landmark recognition systems for mobile robots. This paper answers this question by means of quantitative performance measures. An empirical study is presented in which a number of algorithms are
compared in four environments. The results of this analysis are then applied to the development of a novel landmark recognition system for a Nomad~200 robot. Subsequent experiments demonstrate that the new system obtains a similar level of performance to the best alternative method, but at a much lower computational cost.
Landmark
Mobile Robot Navigation
Dead reckoning
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Based on the situation that the traditional SINS (strapdown inertial navigation system)/CNS (celestial navigation system) integrated navigation system fails to realize all-day and all-weather navigation, this paper proposes a SINS/Landmark integrated navigation method based on landmark attitude determination to solve this problem. This integrated navigation system takes SINS as the basic scheme and uses landmark navigation to correct the error of SINS. The way of the attitude determination is to use the landmark information photographed by the landmark camera to complete feature matching. The principle of the landmark navigation and the process of attitude determination are discussed, and the feasibility of landmark attitude determination is analyzed, including the orthogonality of the attitude transform matrix, as well as the influences of the factors such as quantity and geometric position of landmarks. On this basis, the paper constructs the equations of the SINS/Landmark integrated navigation system, testifies the effectiveness of landmark attitude determination on the integrated navigation by Kalman filter, and improves the navigation precision of the system.
Landmark
Navigation System
Celestial Navigation
Feature (linguistics)
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The cooperation of swarming autonomous mobile robots has received significant interests in recent years. The common goal of research on it is to clarify the minimum capabilities for robots to achieve a given task. Thus, algorithms for mobile robots have been considered on a theoretical model with negative assumptions about each robot capabilities[4, 6]. Concerning the assumptions, each robot is identical (i.e., all robots run the same algorithm), anonymous (i.e., each robot has no IDs to distinguish two robots), oblivious (i.e., each robot has no memory to record past situation) and silent (i.e., each robot has no direct means of communication).
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We propose Landmark-Conscious Voice Navigation as one type of a pedestrian navigation system, which navigate users by only voice guidance. It is necessary to standardize data model in order to use this system widely. In a previous paper[1], we constructed a basic voice navigation system, which uses Open Street Map based data model. In this paper, at first, we conduct an experiment of voice navigation at an underground shopping area of Nagoya Station with two types of landmark descriptions. After that, we discuss what data structure is necessary to describe landmark information for voice navigation. Therefore, we propose to extend IndoorGML1.0 by adding landmark space as a new defined data model for voice navigation. The main contribution of this paper is that we conduct an experiment of voice navigation and research how different landmark descriptions affect users; furthermore, we discuss a IndoorGML extended data model for voice navigation.
Landmark
Turn-by-turn navigation
Navigation System
Mobile Robot Navigation
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To save time, improve flexibility and guarantee accuracy of the navigation system of the mobile robots, a multi-function landmark and a new navigation algorithm are proposed in this paper. With the new algorithm and landmark the mobile robots can be located by only a single landmark, and can be navigated in a large area by serial landmarks. The simple configuration and the convenient material of the landmark increased the system's flexibility and decreased the complexity of the algorithm. From the experimental results it can be concluded that the navigation system has fast navigation speed and high navigation accuracy.
Landmark
Navigation System
Mobile Robot Navigation
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To solve the local trap problems in traditional mobile robot navigation strategy, a algorithm is proposed for mobile robot based on a sonar ring to realize the navigation in an unknown and complex environment. An obstacle avoidance behavior based on Fuzzy logic control and wall-following are presented on the base of building models of sonar data. Using FSM(finite state machine), the navigation status of mobile robot transfer when the information of environment changes, and a corresponding strategy is chosen to realize the navigation task. This algorithm can effectively solve the local trap problems in traditional mobile robot navigation strategy. Experiments on the Pioneer 3DX mobile robot are conducted to evaluate the performance of the algorithm, and good results are obtained.
Mobile Robot Navigation
Obstacle avoidance
Navigation System
Social robot
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This paper introduces history, present situation of mobile robot′s autonomous navigation technology. Based on this some current navigation methods are described in detail. In addition it further studies path planning technique, which is a key technique in autonomous navigation of mobile robot. Afterward artificial intelligence and multi-sensor information fusion technique′s application in mobile robot navigation are discussed. At last it points out the future developing trends on mobile robot autonomous navigation technology.
Mobile Robot Navigation
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One of the major tasks of autonomous robot navigation elimination of robot errors. These errors are caused by imperfections in the design and mechanical implementation of robots. This paper presents experimental and statistical analysis of wheeled robots. The mobile robots consist of three differential drive robots that tested and moved in given trajectories and then the systematic errors of the robots are determined. Finally this research is concluded with comparing the results of statistical analysis for robots and some major parameters are defined for validation of the error correction in considered robots.
Statistical Analysis
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