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Showing papers on "Mobile robot navigation published in 2008"


Journal ArticleDOI
TL;DR: The outline to mapless navigation includes reactive techniques based on qualitative characteristics extraction, appearance-based localization, optical flow, features tracking, plane ground detection/tracking, etc... the recent concept of visual sonar has also been revised.
Abstract: Mobile robot vision-based navigation has been the source of countless research contributions, from the domains of both vision and control. Vision is becoming more and more common in applications such as localization, automatic map construction, autonomous navigation, path following, inspection, monitoring or risky situation detection. This survey presents those pieces of work, from the nineties until nowadays, which constitute a wide progress in visual navigation techniques for land, aerial and autonomous underwater vehicles. The paper deals with two major approaches: map-based navigation and mapless navigation. Map-based navigation has been in turn subdivided in metric map-based navigation and topological map-based navigation. Our outline to mapless navigation includes reactive techniques based on qualitative characteristics extraction, appearance-based localization, optical flow, features tracking, plane ground detection/tracking, etc... The recent concept of visual sonar has also been revised.

649 citations


BookDOI
28 Apr 2008
TL;DR: A Unified Framework for Whole-Body Humanoid Robot Control with Multiple Constraints and Contacts for Robots in Dynamic Environments.
Abstract: Adaptive Multiple Resources Consumption Control for an Autonomous Rover.- Adaptive Snake Robot Locomotion: A Benchmarking Facility for Experiments.- Architecture for Neuronal Cell Control of a Mobile Robot.- The Ares Robot: Case Study of an Affordable Service Robot.- Balancing the Information Gain Against the Movement Cost for Multi-robot Frontier Exploration.- Compiling POMDP Models for a Multimodal Service Robot from Background Knowledge.- Constraint Based Object State Modeling.- A COTS-Based Mini Unmanned Aerial Vehicle (SR-H3) for Security, Environmental Monitoring and Surveillance Operations: Design and Test.- Eyes-Neck Coordination Using Chaos.- Formation Graphs and Decentralized Formation Control of Multi Vehicles with Kinematics Constraints.- Global Urban Localization of an Outdoor Mobile Robot with Genetic Algorithms.- Grip Force Control Using Vision-Based Tactile Sensor for Dexterous Handling.- HNG: A Robust Architecture for Mobile Robots Systems.- Information Relative Map Going Toward Constant Time SLAM.- Measuring Motion Expressiveness in Wheeled Mobile Robots.- Modeling, Simulation and Control of Pneumatic Jumping Robot.- Multilayer Perceptron Adaptive Dynamic Control of Mobile Robots: Experimental Validation.- Path Planning and Tracking Control for an Automatic Parking Assist System.- Performance Evaluation of Ultrasonic Arc Map Processing Techniques by Active Snake Contours.- Planning Robust Landmarks for Sensor Based Motion.- Postural Control on a Quadruped Robot Using Lateral Tilt: A Dynamical System Approach.- Propose of a Benchmark for Pole Climbing Robots.- Rat's Life: A Cognitive Robotics Benchmark.- Reactive Trajectory Deformation to Navigate Dynamic Environments.- Recovery in Autonomous Robot Swarms.- Robot Force/Position Tracking on a Surface of Unknown Orientation.- Scalable Operators for Feature Extraction on 3-D Data.- Semi-autonomous Learning of an RFID Sensor Model for Mobile Robot Self-localization.- A Simple Visual Navigation System with Convergence Property.- Stability of On-Line and On-Board Evolving of Adaptive Collective Behavior.- A Unified Framework for Whole-Body Humanoid Robot Control with Multiple Constraints and Contacts.- Visual Approaches for Handle Recognition.- Visual Top-Down Attention Framework for Robots in Dynamic Environments.- Visual Topological Mapping.- 3D Mapping and Localization Using Leveled Map Accelerated ICP.

301 citations


Journal ArticleDOI
TL;DR: This paper defines a specific type of semantic maps, which integrates hierarchical spatial information and semantic knowledge, and describes how these semantic maps can improve task planning in two ways: extending the capabilities of the planner by reasoning about semantic information, and improving the planning efficiency in large domains.

285 citations


Proceedings ArticleDOI
15 Aug 2008
TL;DR: This study explores how a robotpsilas physical or virtual presence affects unconscious human perception of the robot as a social partner by collaborating on simple book-moving tasks with either a physically present humanoid robot or a video-displayed robot.
Abstract: This study explores how a robotpsilas physical or virtual presence affects unconscious human perception of the robot as a social partner. Subjects collaborated on simple book-moving tasks with either a physically present humanoid robot or a video-displayed robot. Each task examined a single aspect of interaction: greetings, cooperation, trust, and personal space. Subjects readily greeted and cooperated with the robot in both conditions. However, subjects were more likely to fulfill an unusual instruction and to afford greater personal space to the robot in the physical condition than in the video-displayed condition. The same tendencies occurred when the virtual robot was supplemented by disambiguating 3-D information.

250 citations


Book ChapterDOI
01 Jan 2008
TL;DR: This work considers the problem of autonomous navigation in an unstructured outdoor environment, and uses stereo vision as the main sensor to use more distant objects as landmarks for navigation, and to learn and use color and texture models of the environment.
Abstract: We consider the problem of autonomous navigation in an unstructured outdoor environment. The goal is for a small outdoor robot to come into a new area, learn about and map its environment, and move to a given goal at modest speeds (1 m/s). This problem is especially difficult in outdoor, off-road environments, where tall grass, shadows, deadfall, and other obstacles predominate. Not surprisingly, the biggest challenge is acquiring and using a reliable map of the new area. Although work in outdoor navigation has preferentially used laser rangefinders [14,2,6], we use stereo vision as the main sensor. Vision sensors allow us to use more distant objects as landmarks for navigation, and to learn and use color and texture models of the environment, in looking further ahead than is possible with range sensors alone.

215 citations


Book ChapterDOI
29 Jan 2008
TL;DR: The focus here is on blind navigation in large-scale, unfamiliar environments, but the technology discussed can be used in well-known spaces and may be useful to those with low vision.
Abstract: The ability to navigate from place to place is an integral part of daily life. Most people would acknowledge that vision plays a critical role, but would have great difficulty in identifying the visual information they use, or when they use it. Although it is easy to imagine getting around without vision in well-known environments, such as walking from the bedroom to the bathroom in the middle of the night, few people have experienced navigating large-scale, unfamiliar environments nonvisually. Imagine, for example, being blindfolded and finding your train in New York’s Grand Central Station. Yet, blind people travel independently on a daily basis. To facilitate safe and efficient navigation, blind individuals must acquire travel skills and use sources of nonvisual environmental information that are rarely considered by their sighted peers. How do you avoid running into the low-hanging branch over the sidewalk, or falling into the open manhole? When you are walking down the street, how do you know when you have reached the post office, the bakery, or your friend’s house? The purpose of this chapter is to highlight some of the navigational technologies available to blind individuals to support independent travel. Our focus here is on blind navigation in large-scale, unfamiliar environments, but the technology discussed can also be used in well-known spaces and may be useful to those with low vision.

199 citations


Journal ArticleDOI
TL;DR: A novel neural-dynamics-based approach is proposed for real-time map building and CCN of autonomous mobile robots in a completely unknown environment that is capable of planning more reasonable and shorter collision-free complete coverage paths in unknown environments.
Abstract: Complete coverage navigation (CCN) requires a special type of robot path planning, where the robots should pass every part of the workspace. CCN is an essential issue for cleaning robots and many other robotic applications. When robots work in unknown environments, map building is required for the robots to effectively cover the complete workspace. Real-time concurrent map building and complete coverage robot navigation are desirable for efficient performance in many applications. In this paper, a novel neural-dynamics-based approach is proposed for real-time map building and CCN of autonomous mobile robots in a completely unknown environment. The proposed model is compared with a triangular-cell-map-based complete coverage path planning method (Oh et al., 2004) that combines distance transform path planning, wall-following algorithm, and template-based technique. The proposed method does not need any templates, even in unknown environments. A local map composed of square or rectangular cells is created through the neural dynamics during the CCN with limited sensory information. From the measured sensory information, a map of the robot's immediate limited surroundings is dynamically built for the robot navigation. In addition, square and rectangular cell map representations are proposed for real-time map building and CCN. Comparison studies of the proposed approach with the triangular-cell-map-based complete coverage path planning approach show that the proposed method is capable of planning more reasonable and shorter collision-free complete coverage paths in unknown environments.

195 citations


Journal ArticleDOI
TL;DR: The proposed approach in this paper involves a new grid-based map model called ''memory grid'' and a new behavior-based navigation method called ''minimum risk method'' that adopts a strategy of multi-behavior coordination in which a novel path-searching behavior is developed to recommend the region offering the minimum risk.

148 citations


Journal ArticleDOI
TL;DR: This paper discusses how RFID tags are placed in the 3-D space so that the lines linking their projections on the ground define the ldquofree waysrdquo along which the robot can (or is desired to) move.
Abstract: This paper presents an innovative mobile robot navigation technique using radio frequency identification (RFID) technology. Navigation based on processing some analog features of an RFID signal is a promising alternative to different types of navigation methods in the state of the art. The main idea is to exploit the ability of a mobile robot to navigate a priori unknown environments without a vision system and without building an approximate map of the robot workspace, as is the case in most other navigation algorithms. This paper discusses how this is achieved by placing RFID tags in the 3-D space so that the lines linking their projections on the ground define the ldquofree waysrdquo along which the robot can (or is desired to) move. The suggested algorithm is capable of reaching a target point in its a priori unknown workspace, as well as tracking a desired trajectory with a high precision. The proposed solution offers a modular, computationally efficient, and cost-effective alternative to other navigation techniques for a large number of mobile robot applications, particularly for service robots, such as, for instance, in large offices and assembly lines. The effectiveness of the proposed approach is illustrated through a number of computer simulations considering testbeds of various complexities.

147 citations


Patent
13 Mar 2008
TL;DR: In this paper, an environment map and a robot designator are presented to a user and a control intermediary analyzes a relative position between the task designators and the robot and communicates target achievement information to the robot.
Abstract: Systems, methods, and user interfaces are used for controlling a robot. An environment map and a robot designator are presented to a user. The user may place, move, and modify task designators on the environment map. The task designators indicate a position in the environment map and indicate a task for the robot to achieve. A control intermediary links task designators with robot instructions issued to the robot. The control intermediary analyzes a relative position between the task designators and the robot. The control intermediary uses the analysis to determine a task-oriented autonomy level for the robot and communicates target achievement information to the robot. The target achievement information may include instructions for directly guiding the robot if the autonomy level indicates low robot initiative and may include instructions for directing the robot to determine a robot plan for achieving the task if the autonomy level indicates high robot initiative.

126 citations


Journal ArticleDOI
TL;DR: This work presents a system for generating three-dimensional environment maps from data taken by stereo vision using a method for precise segmentation of range data into planar segments based on the algorithm of scan-line grouping extended to cope with the noise dynamics of stereo vision.
Abstract: A humanoid robot that can go up and down stairs, crawl underneath obstacles or simply walk around requires reliable perceptual capabilities for obtaining accurate and useful information about its surroundings. In this work we present a system for generating three-dimensional (3D) environment maps from data taken by stereo vision. At the core is a method for precise segmentation of range data into planar segments based on the algorithm of scan-line grouping extended to cope with the noise dynamics of stereo vision. In off-line experiments we demonstrate that our extensions achieve a more precise segmentation. When compared to a previously developed patch-let method, we obtain a richer segmentation with a higher accuracy while also requiring far less computations. From the obtained segmentation we then build a 3D environment map using occupancy grid and floor height maps. The resulting representation classifies areas into one of six different types while also providing object height information. We apply our perception method for the navigation of the humanoid robot QRIO and present experiments of the robot stepping through narrow space, walking up and down stairs and crawling underneath a table.

Proceedings ArticleDOI
03 Dec 2008
TL;DR: A system that leverages an online collection of geotagged photographs to automatically generate navigational instructions that are presented to the user as a sequence of images of landmarks augmented with directional instructions.
Abstract: Mobile phones are an attractive platform for landmark-based pedestrian navigation systems. To be practical, such a system must be able to automatically generate lightweight directions that can be displayed on these mobile devices. We present a system that leverages an online collection of geotagged photographs to automatically generate navigational instructions. These are presented to the user as a sequence of images of landmarks augmented with directional instructions. Both the landmark selection and image augmentation are done automatically. We present a user study that indicates these generated directions are beneficial to users and suggest areas for future improvement.

Journal IssueDOI
01 Jun 2008
TL;DR: An effective algorithm for state space sampling utilizing a model-based trajectory generation approach is presented that enables high-speed navigation in highly constrained and-or partially known environments such as trails, roadways, and dense off-road obstacle fields.
Abstract: Sampling in the space of controls or actions is a well-established method for ensuring feasible local motion plans. However, as mobile robots advance in performance and competence in complex environments, this classical motion-planning technique ceases to be effective. When environmental constraints severely limit the space of acceptable motions or when global motion planning expresses strong preferences, a state space sampling strategy is more effective. Although this has been evident for some time, the practical question is how to achieve it while also satisfying the severe constraints of vehicle dynamic feasibility. The paper presents an effective algorithm for state space sampling utilizing a model-based trajectory generation approach. This method enables high-speed navigation in highly constrained and-or partially known environments such as trails, roadways, and dense off-road obstacle fields. © 2008 Wiley Periodicals, Inc.

Journal ArticleDOI
TL;DR: Some optimal path planning algorithms for navigating mobile rectangular robot among obstacles and weighted regions are presented and can be easily extended to the dynamic collision avoidance problem among multiple autonomous robots or path planning in the 3-D space.
Abstract: Some optimal path planning algorithms for navigating mobile rectangular robot among obstacles and weighted regions are presented. The approach is based on a higher geometry maze routing algorithm. Starting from a top view of a workspace with obstacles, the so-called free workspace is first obtained by virtually expanding the obstacles in the image. After that, an 8-geomerty maze routing algorithm is applied to obtain an optimal collision-free path with linear time and space complexities. The proposed methods cannot only search an optimal path among various terrains but also find an optimal path for the 2-D piano mover's problem with 3 DOF. Furthermore, the algorithm can be easily extended to the dynamic collision avoidance problem among multiple autonomous robots or path planning in the 3-D space.

01 Jan 2008
TL;DR: An algorithm for path planning to a target for mobile robot in unknown environment that allows a mobile robot to navigate through static obstacles, and finding the path in order to reach the target without collision is presented.
Abstract: this present work, we present an algorithm for path planning to a target for mobile robot in unknown environment. The proposed algorithm allows a mobile robot to navigate through static obstacles, and finding the path in order to reach the target without collision. This algorithm provides the robot the possibility to move from the initial position to the final position (target). The proposed path finding strategy is designed in a grid-map form of an unknown environment with static unknown obstacles. The robot moves within the unknown environment by sensing and avoiding the obstacles coming across its way towards the target. When the mission is executed, it is necessary to plan an optimal or feasible path for itself avoiding obstructions in its way and minimizing a cost such as time, energy, and distance. The proposed path planning must make the robot able to achieve these tasks: to avoid obstacles, and to make ones way toward its target. The algorithms are implemented in Borland C++, afterwards tested with visual basic and DELPHI programming language; whereby the environment is studied in a two dimensional coordinate system. The simulation part is an approach to the real expected result; this part is done using C++ to recognize all objects within the environment and since it is suitable for graphic problems. Taking the segmented environment issued from C++ development, the algorithm permit the robot to move from the initial position to the desired position following an estimated trajectory using visual basic and Delphi language.

Journal ArticleDOI
TL;DR: A novel application of robotic technologies to education is presented, where the real world situatedness of a robot is used to teach non-robotic related subjects, such as math and physics.
Abstract: So far, most of the applications of robotic technology to education have mainly focused on supporting the teaching of subjects that are closely related to the Robotics field, such as robot programming, robot construction, or mechatronics. Moreover, most of the applications have used the robot as an end or a passive tool of the learning activity, where the robot has been constructed or programmed. In this paper, we present a novel application of robotic technologies to education, where we use the real world situatedness of a robot to teach non-robotic related subjects, such as math and physics. Furthermore, we also provide the robot with a suitable degree of autonomy to actively guide and mediate in the development of the educational activity. We present our approach as an educational framework based on a collaborative and constructivist learning environment, where the robot is able to act as an interaction mediator capable of managing the interactions occurring among the working students. We illustrate the use of this framework by a 4-step methodology that is used to implement two educational activities. These activities were tested at local schools with encouraging results. Accordingly, the main contributions of this work are: i) A novel use of a mobile robot to illustrate and teach relevant concepts and properties of the real world; ii) A novel use of robots as mediators that autonomously guide an educational activity using a collaborative and constructivist learning approach; iii) The implementation and testing of these ideas in a real scenario, working with students at local schools.


Journal ArticleDOI
TL;DR: This paper presents the design of a preference-based fuzzy behavior system for navigation control of robotic vehicles using the multivalued logic framework and shows that the proposed method allows the robot to smoothly and effectively navigate through cluttered environments such as dense forests.

Proceedings ArticleDOI
12 Mar 2008
TL;DR: An initial field trial with a prototype of a semi-autonomous communication robot at a train station revealed that the operator-requesting mechanism correctly requested operator's help in 85% of the necessary situations and provided the opportunity to gather user data for the further development of natural behaviors for such robots operating in real environments.
Abstract: This paper reports an initial field trial with a prototype of a semi-autonomous communication robot at a train station. We developed an operator-requesting mechanism to achieve semi-autonomous operation for a communication robot functioning in real environments. The operator-requesting mechanism autonomously detects situations that the robot cannot handle by itself; a human operator helps by assuming control of the robot. This approach gives semi-autonomous robots the ability to function naturally with minimum human effort. Our system consists of a humanoid robot and ubiquitous sensors. The robot has such basic communicative behaviors as greeting and route guidance. The experimental results revealed that the operator-requesting mechanism correctly requested operator's help in 85% of the necessary situations; the operator only had to control 25% of the experiment time in the semi-autonomous mode with a robot system that successfully guided 68% of the passengers. At the same time, this trial provided the opportunity to gather user data for the further development of natural behaviors for such robots operating in real environments.

Journal ArticleDOI
01 Jan 2008
TL;DR: The results presented in this article strongly indicate the potential of including the intelligent navigator as the core algorithm for INS/GPS integrated land vehicle navigation systems.
Abstract: The Kalman filter (KF) has been implemented as the primary integration scheme of the global positioning system (GPS) and inertial navigation systems (INS) for many land vehicle navigation and positioning applications. However, it has been reported that KF-based techniques have certain limitations, which reflect on the position error accumulation during GPS signal outages. Therefore, this article exploits the idea of incorporating artificial neural networks to develop an alternative INS/GPS integration scheme, the intelligent navigator, for next generation land vehicle navigation and positioning applications. Real land vehicle test results demonstrated the capability of using stored navigation knowledge to provide real-time reliable positioning information for stand-alone INS-based navigation for up to 20min with errors less than 16m (as compared to 2.6km in the case of the KF). For relatively short GPS outages, the KF was superior to the intelligent navigator for up to 30s outages. In contrast, the intelligent navigator was superior to the KF when the length of GPS outages was extended to 90s. The average improvement of the intelligent navigator reached 60% in the latter scenario. The results presented in this article strongly indicate the potential of including the intelligent navigator as the core algorithm for INS/GPS integrated land vehicle navigation systems.

Proceedings ArticleDOI
22 Sep 2008
TL;DR: This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long- term and short-term memory concepts, with omni-directional vision as the external sensor.
Abstract: This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor.

Proceedings ArticleDOI
30 Nov 2008
TL;DR: This paper begins with very basic wall follower logic to solve the maze and gradually improves the algorithm to accurately solve the Maze in shortest time with some more intelligence.
Abstract: The problem of micro-mouse is 30 years old but its importance in the field of robotics is unparalleled, as it requires a complete analysis & proper planning to be solved. This paper covers one of the most important areas of robot, ldquodecision making algorithmrdquo or in lay-manpsilas language, ldquorobot intelligencerdquo. For starting in the field of micro-mouse it is very difficult to begin with highly sophisticated algorithms. This paper begins with very basic wall follower logic to solve the maze. And gradually improves the algorithm to accurately solve the maze in shortest time with some more intelligence. The Algorithm is developed up to some sophisticated level as flood-fill algorithm. The paper would help all the beginners in this fascinating field, as they proceed towards development of the ldquobrain of the systemrdquo, particularly for robots concerned with path planning and navigation.

Proceedings ArticleDOI
14 Oct 2008
TL;DR: A new method for reactive collision avoidance for mobile robots in complex and cluttered environments by adapting the ldquodivide and conquerrdquo approach of the nearness-diagram+ navigation method to generate a single motion law which applies for all navigational situations.
Abstract: This paper presents a new method for reactive collision avoidance for mobile robots in complex and cluttered environments. Our technique is to adapt the ldquodivide and conquerrdquo approach of the nearness-diagram+ navigation (ND+) method to generate a single motion law which applies for all navigational situations. The resulting local path planner considers all the visible obstacles surrounding the robot, not just the closest two. With these changes our new navigation method generates smoother motion while avoiding obstacles. Results from comparisons with ND+ are presented as are experiments using Erratic mobile robots.

Journal ArticleDOI
01 Aug 2008
TL;DR: Reservoir Computing techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods.
Abstract: Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Journal ArticleDOI
TL;DR: A joint approach for robot navigation with collision avoidance, pose estimation and map building with a 2.5D Photonic Mixer Device (PMD)-camera combined with a high-resolution spherical camera.
Abstract: In this paper, we describe a joint approach for robot navigation with collision avoidance, pose estimation and map building with a 2.5D Photonic Mixer Device (PMD)-camera combined with a high-resolution spherical camera. The cameras are mounted at the front of the robot with a certain inclination angle. The navigation and map building consists of two steps: when entering new terrain the robot first scans the surrounding. Simultaneously a 3D-panorama is generated from the PMD-images. In the second step, the robot moves along the pre-defined path, using the PMD-camera for collision avoidance and a combined Structure-from-Motion (SfM) and model-tracking approach for self-localisation. The computed poses of the robot are simultaneously used for map building with new measurements from the PMD-camera.

Proceedings ArticleDOI
George Fitzmaurice1, Justin Matejka1, Igor Mordatch1, Azam Khan1, Gordon Kurtenbach1 
15 Feb 2008
TL;DR: This paper describes the major properties needed for safe navigation, the features implemented to realize these properties, and usability tests on the effectiveness of these features conclude that indeed these properties do improve the learning experience for users that are new to 3D.
Abstract: Typical commercial 3D CAD tools provide modal tools such as pan, zoom, orbit, look, etc. to facilitate freeform navigation in a 3D scene. Mastering these navigation tools requires a significant amount of learning and even experienced computer users can find learning confusing and error-prone. To address this we have developed a concept called "Safe 3D Navigation" where we augment these modal tools with properties to reduce the occurance of confusing situations and improve the learning experience. In this paper we describe the major properties needed for safe navigation, the features we implemented to realize these properties, and usability tests on the effectiveness of these features. We conclude that indeed these properties do improve the learning experience for users that are new to 3D. Furthermore, many of the features we implemented for safe navigation are also very popular with experienced 3D users. As a result, these features have been integrated into six commercial 3D CAD applications and we recommend other application developers include these features to improve 3D navigation.

Journal ArticleDOI
TL;DR: In this article, hybrid control architecture is conceived via combining reactive and deliberate control using a hierarchical Q-learning (HQL) algorithm.
Abstract: Autonomous mobile robots have been widely studied and applied not only as a test bed to academically demonstrate the achievement of artificial intelligence but also as an essential component of industrial and home automation. Mobile robots have many potential applications in routine or dangerous tasks such as delivery of supplies in hospitals, cleaning of offices, and operations in a nuclear plant. One of the fundamental and critical research areas in mobile robotics is navigation, which generally includes local navigation and global navigation. Local navigation, often called reactive control, learns or plans the local paths using the current sensory inputs without prior complete knowledge of the environment. Global navigation, often called deliberate control, learns or plans the global paths based on a relatively abstract and complete knowledge about the environment. In this article, hybrid control architecture is conceived via combining reactive and deliberate control using a hierarchical Q-learning (HQL) algorithm.

Proceedings ArticleDOI
30 Sep 2008
TL;DR: This simple robot can understand control commands spoken in a natural way, and execute the corresponding action, and the method is proved efficient enough for real-time operation.
Abstract: In this paper, a speech-control robot system has been presented. This simple system shows the ability to apply speech recognition techniques to the control application. Our robot can understand control commands spoken in a natural way, and execute the corresponding action. Such a mobile robot has potential for application in somewhere voice communication plays a crucial role. The method is proved efficient enough for real-time operation.

Proceedings ArticleDOI
14 Oct 2008
TL;DR: The construction of a small portable personal navigation device which utilizes a commercial Ultra-Wideband (UWB) asset tracking system to support real-time location and navigation information is described.
Abstract: Indoor navigation technology is needed to support seamless mobility for the visually impaired. A small portable personal navigation device that provides current position, useful contextual wayfinding information about the indoor environment and directions to a destination would greatly improve access and independence for people with low vision. This paper describes the construction of such a device which utilizes a commercial Ultra-Wideband (UWB) asset tracking system to support real-time location and navigation information. Human trials were conducted to assess the efficacy of the system by comparing target-finding performance between blindfolded subjects using the navigation system for real-time guidance, and blindfolded subjects who only received speech information about their local surrounds but no route guidance information (similar to that available from a long cane or guide dog). A normal vision control condition was also run. The time and distance traveled was measured in each trial and a point-back test was performed after goal completion to assess cognitive map development. Statistically significant differences were observed between the three conditions in time and distance traveled; with the navigation system and the visual condition yielding the best results, and the navigation system dramatically outperforming the non-guided condition.

Book
01 Jan 2008
TL;DR: The aim of the work was to determine the extent to which hippocampal models can be used to provide a robot with functional mapping and navigation capabilities in real world environments.
Abstract: This book describes the development of a robot mapping and navigation system inspired by models of the neural mechanisms underlying spatial navigation in the rodent hippocampus. Computational models of animal navigation systems have traditionally had limited performance when implemented on robots. The aim of the work was to determine the extent to which hippocampal models can be used to provide a robot with functional mapping and navigation capabilities in real world environments. The focus of the research was on achieving practical robot performance, rather than maintaining biological plausibility.