bluuebunny/crossref_metadata_2025 huggingface dataset:
Task Characterisation and Cross-Platform Programming Through System Identification
Authors: Kyriacou Theocharis , Nehmzow Ulrich , Iglesias Roberto , Billings Steve
Published: March 2012

Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, it is subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour, based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process.

Such iterative refinement could be reduced, we argue, if a more profound theoretical understanding of robot-environment interaction existed. In this paper, we therefore present a modelling method that generates a faithful model of a robot's interaction with its environment, based on data logged while observing a physical robot's behaviour. Because this modelling method — nonlinear modelling using polynomials — is commonly used in the engineering discipline of system identification, we refer to it here as “robot identification”.

We show in this paper that using robot identification to obtain a computer model of robot-environment interaction offers several distinct advantages: Very compact representations (one-line programs) of the robot control program are generated The model can be analysed, for example through sensitivity analysis, leading to a better understanding of the essential parameters underlying the robot's behaviour, and The generated, compact robot code can be used for cross-platform robot programming, allowing fast transfer of robot code from one type of robot to another.

We demonstrate these points through experiments with a Magellan Pro and a Nomad 200 mobile robot.
Psychologically Inspired Sensory-Motor Development in Early Robot Learning
Authors: Lee M.H. , Meng Q.
Published: March 2012

We present an implementation of a model of very early sensory-motor development, guided by results from developmental psychology. Behavioural acquisition and growth is demonstrated through constraint-lifting mechanisms initiated by global state variables. The results show how staged competence can be shaped by qualitative behaviour changes produced by anatomical, computational and maturational constraints.
A Biomimetic Haptic Sensor
Authors: Pearson Martin J. , Gilhespy Ian , Melhuish Chris , Mitchinson Ben , Nibouche Mokhtar , Pipe Anthony G. , Prescott Tony J.
Published: March 2012

The design and implementation of the periphery of an artificial whisker sensory system is presented. It has been developed by adopting a biomimetic approach to model the structure and function of rodent facial vibrissae. The artificial vibrissae have been formed using composite materials and have the ability to be actively moved or whisked. The sensory structures at the root of real vibrissae has been modelled and implemented using micro strain gauges and Digital Signal Processors. The primary afferents and vibrissal trigeminal ganglion have been modelled using empirical data taken from electrophysiological measurements, and implemented in real-time using a Field Programmable Gate Array. Pipelining techniques were employed to maximise the utility of the FPGA hardware. The system is to be integrated into a more complete whisker sensory model, including neural structures within the central nervous system, which can be used to orient a mobile robot.
Perceptual Perspective Taking and Action Recognition
Authors: Johnson Matthew , Demiris Yiannis
Published: March 2012

Robots that operate in social environments need to be able to recognise and understand the actions of other robots, and humans, in order to facilitate learning through imitation and collaboration. The success of the simulation theory approach to action recognition and imitation relies on the ability to take the perspective of other people, so as to generate simulated actions from their point of view. In this paper, simulation of visual perception is used to re-create the visual egocentric sensory space and egocentric behaviour space of an observed agent, and through this increase the accuracy of action recognition. To demonstrate the approach, experiments are performed with a robot attributing perceptions to and recognising the actions of a second robot.
A Novel Penetration System for in situ Astrobiological Studies
Authors: Gao Yang , Ellery Alex , Jaddou Mustafa , Vincent Julian , Eckersley Steven
Published: March 2012

Due to ultraviolet flux in the surface layers of most solar bodies, future astrobiological research is increasingly seeking to conduct subsurface penetration and drilling to detect chemical signature for extant or extinct life. To address this issue, we present a micro-penetrator concept (mass < 10 kg) that is suited for extraterrestrial planetary deployment and in situ investigation of chemical and physical properties. The instrumentation in this concept is a bio-inspired drill to access material beneath sterile surface layer for biomarker detection. The proposed drill represents a novel concept of two-valve-reciprocating motion, inspired by the working mechanism of wood wasp ovipositors. It is lightweight (0.5 kg), driven at low power (3 W), and able to drill deep (1-2 m). Tests have shown that the reciprocating drill is feasible and has potential of improving drill efficiency without using any external force. The overall penetration system provides a small, light and energy efficient solution to in situ astrobiological studies, which is crucial for space engineering. Such a micro-penetrator can be used for exploration of terrestrial-type planets or other small bodies of the solar system with the minimum of modifications.
A Novel Exploration Algorithm Based on a Improvement Strategy
Authors: Gartshore Rachel , Palmer Phil , Illingworth John
Published: March 2012

In this paper we present a strategy for the problem of exploring an unknown 2D environment. Existing techniques can be methodical, goal oriented or non-reactive to additional knowledge received at each new viewpoint. We present an approach which is not goal driven, but rather seeks new unseen areas to view and explore.

The novelty of the strategy presented is the use of a view-improvement technique along with an optimal viewpoint planning method for the calculation and selection of the next-best-viewpoint. The strategy is designed for a sensor system with a limited field-of-view. Example explorations are presented and we demonstrate that the strategy finds new areas to view without exhaustive searching.
Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search
Authors: Ata Atef A. , Myo Thi Rein
Published: March 2012

Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.
Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation
Authors: Kia Chua , Arshad Mohd Rizal
Published: March 2012

This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline) in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.
Obstacle Avoidance in Groping Locomotion of a Humanoid Robot
Authors: Yussof Hanafiah , Yamano Mitsuhiro , Nasu Yasuo , Mitobe Kazuhisa , Ohka Masahiro
Published: March 2012

This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robot's control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robot's leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a wall's surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.
Study of Self-Organization Model of Multiple Mobile Robot
Authors: Xian-yi Ceng , Shu-qin Li , De-shen Xia
Published: March 2012

A good organization model of multiple mobile robot should be able to improve the efficiency of the system, reduce the complication of robot interactions, and detract the difficulty of computation. From the sociology aspect of topology, structure and organization, this paper studies the multiple mobile robot organization formation and running mechanism in the dynamic, complicated and unknown environment. It presents and describes in detail a Hierarchical-Web Recursive Organization Model (HWROM) and forming algorithm. It defines the robot society leader; robotic team leader and individual robot as the same structure by the united framework and describes the organization model by the recursive structure. The model uses task-oriented and top-down method to dynamically build and maintain structures and organization. It uses market-based techniques to assign task, form teams and allocate resources in dynamic environment. The model holds several characteristics of self-organization, dynamic, conciseness, commonness and robustness.
Learning Innovative Routes for Mobile Robots in Dynamic Partially Unknown Environments
Authors: Heero Kristo , Aabloo Alvo , Kruusmaa Maarja
Published: March 2012

This paper examines path planning strategies in partially unknown dynamic environemnts and introduces an approach to learning innovative routes. The approach is verified against shortest path planning with a distance transform algorithm, local and global replanning and suboptimal route following in unknown, partially unknown, static and dynamic environments. We show that the learned routes are more reliable and when traversed repeatedly the robot's behaviour becomes more predictable. The test results also suggest that the robot's behaviour depends on knowledge about the environemnt but not about the path planning strategy used.
Robot Swarms in an Uncertain World: Controllable Adaptability
Authors: Bogatyreva Olga , Shillerov Alexandr
Published: March 2012

There is a belief that complexity and chaos are essential for adaptability. But life deals with complexity every moment, without the chaos that engineers fear so, by invoking goal-directed behaviour. Goals can be programmed. That is why living organisms give us hope to achieve adaptability in robots. In this paper a method for the description of a goal-directed, or programmed, behaviour, interacting with uncertainty of environment, is described. We suggest reducing the structural (goals, intentions) and stochastic components (probability to realise the goal) of individual behaviour to random variables with nominal values to apply probabilistic approach. This allowed us to use a Normalized Entropy Index to detect the system state by estimating the contribution of each agent to the group behaviour. The number of possible group states is 27. We argue that adaptation has a limited number of possible paths between these 27 states. Paths and states can be programmed so that after adjustment to any particular case of task and conditions, adaptability will never involve chaos. We suggest the application of the model to operation of robots or other devices in remote and/or dangerous places.
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot
Authors: Choomuang Rerngwut , Afzulpurkar Nitin
Published: March 2012

This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc.) and/or non-systematic errors (ground plane, wheel-slip etc.) contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles.
A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation
Authors: Li Shu-qin , Shuai Lan , Cheng Xian-yi , Tang Zhen-min , Yang Jing-yu
Published: March 2012

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model.
Robust Motion Control for Mobile Manipulator Using Resolved Acceleration and Proportional-Integral Active Force Control
Authors: Mailah Musa , Pitowarno Endra , Jamaluddin Hishamuddin
Published: March 2012

A resolved acceleration control (RAC) and proportional-integral active force control (PIAFC) is proposed as an approach for the robust motion control of a mobile manipulator (MM) comprising a differentially driven wheeled mobile platform with a two-link planar arm mounted on top of the platform. The study emphasizes on the integrated kinematic and dynamic control strategy in which the RAC is used to manipulate the kinematic component while the PIAFC is implemented to compensate the dynamic effects including the bounded known/unknown disturbances and uncertainties. The effectivenss and robustness of the proposed scheme are investigated through a rigorous simulation study and later complemented with experimental results obtained through a number of experiments performed on a fully developed working prototype in a laboratory environment. A number of disturbances in the form of vibratory and impact forces are deliberately introduced into the system to evaluate the system performances. The investigation clearly demonstrates the extreme robustness feature of the proposed control scheme compared to other systems considered in the study.
A Hybrid Three Layer Architecture for Fire Agent Management in Rescue Simulation Environment
Authors: Geramifard Alborz , Nayeri Peyman , Zamani-Nasab Reza , Habibi Jafar
Published: March 2012

This paper presents a new architecture called FAIS for implementing intelligent agents cooperating in a special Multi Agent environment, namely the RoboCup Rescue Simulation System. This is a layered architecture which is customized for solving fire extinguishing problem. Structural decision making algorithms are combined with heuristic ones in this model, so it's a hybrid architecture.
Control of a Lightweight Flexible Robotic Arm Using Sliding Modes
Authors: Etxebarria Victor , Sanz Arantza , Lizarraga Ibone
Published: March 2012

This paper presents a robust control scheme for flexible link robotic manipulators, which is based on considering the flexible mechanical structure as a system with slow (rigid) and fast (flexible) modes that can be controlled separately. The rigid dynamics is controlled by means of a robust sliding-mode approach with well-established stability properties while an LQR optimal design is adopted for the flexible dynamics. Experimental results show that this composite approach achieves good closed loop tracking properties both for the rigid and the flexible dynamics.
Wavefront Propagation and Fuzzy Based Autonomous Navigation
Authors: Al-Jumaily Adel , Leung Cindy
Published: March 2012

Path planning and obstacle avoidance are the two major issues in any navigation system. Wavefront propagation algorithm, as a good path planner, can be used to determine an optimal path. Obstacle avoidance can be achieved using possibility theory. Combining these two functions enable a robot to autonomously navigate to its destination. This paper presents the approach and results in implementing an autonomous navigation system for an indoor mobile robot. The system developed is based on a laser sensor used to retrieve data to update a two dimensional world model of therobot environment. Waypoints in the path are incorporated into the obstacle avoidance. Features such as ageing of objects and smooth motion planning are implemented to enhance efficiency and also to cater for dynamic environments.
Modular Adaptive System Based on a Multi-Stage Neural Structure for Recognition of 2D Objects of Discontinuous Production
Authors: Topalova I.
Published: March 2012

This is a presentation of a new system for invariant recognition of 2D objects with overlapping classes, that can not be effectively recognized with the traditional methods. The translation, scale and partial rotation invariant contour object description is transformed in a DCT spectrum space. The obtained frequency spectrums are decomposed into frequency bands in order to feed different BPG neural nets (NNs). The NNs are structured in three stages - filtering and full rotation invariance; partial recognition; general classification. The designed multi-stage BPG Neural Structure shows very good accuracy and flexibility when tested with 2D objects used in the discontinuous production. The reached speed and the opportunuty for an easy restructuring and reprogramming of the system makes it suitable for application in different applied systems for real time work.
Effects of Initial Stance of Quadruped Trotting on Walking Stability
Authors: He Dongqing , Ma Peisun
Published: March 2012

It is very important for quadruped walking machine to keep its stability in high speed walking. It has been indicated that moment around the supporting diagonal line of quadruped in trotting gait largely influences walking stability. In this paper, moment around the supporting diagonal line of quadruped in trotting gait is modeled and its effects on body attitude are analyzed. The degree of influence varies with different initial stances of quadruped and we get the optimal initial stance of quadruped in trotting gait with maximal walking stability. Simulation results are presented.
The Automated Threaded Fastening Based on On-line Identification
Authors: Klingajay Mongkorn , Giannoccaro Nicolas Ivan
Published: March 2012

The principle of the thread fastenings have been known and used for decades with the purpose of joining one component to another. Threaded fastenings are popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually. It is a difficult problem to automat. As a result there is very little published research on automating threaded fastenings, and most research on automated assembly focus on the peg-in-hole assembly problem. This paper investigates the problem of automated monitoring of the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw insertions. However, the model requires parameters on the screw dimensions and plate material properties are difficult to measure. This paper presents a study on on-line identification during screw fastenings. An identification methodology for two unknown parameter estimation during a self-tapping screw insertion process is presented. It is shown that friction and screw properties required by the model can be reliably estimated on-line. Experimental results are presented to validate the identification procedure.
Design and Implementation of a General Decision-Making Model in RoboCup Simulation
Authors: Wang Changda , Chen Xianyi , Zhao Xibin , Ju Shiguang
Published: March 2012

The study of the collaboration, coordination and negotiation among different agents in a multi-agent system (MAS) has always been the most challenging yet popular in the research of distributed artificial intelligence. In this paper, we will suggest for RoboCup simulation, a typical MAS, a general decision-making model, rather than define a different algorithm for each tactic (e.g. ball handling, pass, shoot and interception, etc.) in soccer games as most RoboCup simulation teams did. The general decision-making model is based on two critical factors in soccer games: the vertical distance to the goal line and the visual angle for the goalpost. We have used these two parameters to formalize the defensive and offensive decisions in RoboCup simulation and the results mentioned above had been applied in NOVAURO®, original name is UJDB, a RoboCup simulation team of Jiangsu University, whose decision-making model, compared with that of Tsinghua University, the world champion team in 2001, is a universal model and easier to be implemented.
Space Robotics
Authors: Ellery Alex
Published: March 2012

In this second of three short papers, I introduce some of the basic concepts of space robotics with an emphasis on some specific challenging areas of research that are peculiar to the application of robotics to space infrastructure development. The style of these short papers is pedagogical and the concepts in this paper are developed from fundamental manipulator robotics. This second paper considers the application of space manipulators to on-orbit servicing (OOS), an application which has considerable commercial application. I provide some background to the notion of robotic on-orbit servicing and explore how manipulator control algorithms may be modified to accommodate space manipulators which operate in the micro-gravity of space.
A Dynamical Training and Design Simulator for Active Catheters
Authors: Dumont Georges , Kuehl Christofer
Published: March 2012

This work addresses the design of an active multi-link micro-catheter actuated by Shape Memory Alloy (SMA) micro actuators. This may be a response to one medical major demand on such devices, which will be useful for surgical explorations and interventions. In this paper, we focus on a training and design simulator dedicated to such catheters. This simulator is based on an original simulation platform (OpenMASK). The catheter is a robotic system, which is evaluated by a dynamical simulation addressing a navigation task in its environment. The design of the prototype and its mechanical model are presented. We develop an interaction model for contact. This model uses a real medical database for which distance cartography is proposed. Then we focus on an autonomous control model based on a multi-agent approach and including the behaviour description of the SMA actuators. Results of mechanical simulations including interaction with the ducts are presented. Furthermore, the interest of such a simulator is presented by applying virtual prototyping techniques for the design optimization. This optimization process is achieved by using genetic algorithms at different stages with respect to the specified task.
Learning to Automatically Detect Features for Mobile Robots Using Second-Order Hidden Markov Models
Authors: Aycard Olivier , Mari Jean-Francois , Washington Richard
Published: March 2012

In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T-intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.
FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems
Authors: Karadeniz Toygar , Akin Levent
Published: March 2012

Finding optimal solutions to Partially Observable Markov Decision Problems is known to be NP-hard. This paper describes a novel neuro-fuzzy approach to obtain fast, robust and easily interpreted solutions by utilizing a combination of several learning techniques including neural networks, fuzzy decision making and Q-learning.
Backstepping Based Trajectory Tracking Control of a Four Wheeled Mobile Robot
Authors: Kumar Umesh , Sukavanam Nagarajan
Published: March 2012

For a four wheeled mobile robot a trajectory tracking concept is developed based on its kinematics. A trajectory is a time–indexed path in the plane consisting of position and orientation. The mobile robot is modeled as a non holonomic system subject to pure rolling, no slip constraints. To facilitate the controller design the kinematic equation can be converted into chained form using some change of co-ordinates. From the kinematic model of the robot a backstepping based tracking controller is derived. Simulation results demonstrate such trajectory tracking strategy for the kinematics indeed gives rise to an effective methodology to follow the desired trajectory asymptotically.
Soil Parameter Identification and Driving Force Prediction for Wheel-Terrain Interaction
Authors: Hutangkabodee Suksun , Zweiri Yahya , Seneviratne Lakmal , Althoefer Kaspar
Published: March 2012

This paper considers wheeled vehicles traversing unknown terrain, and proposes an approach for identifying the unknown soil parameters required for vehicle driving force prediction (drawbar pull prediction). The predicted drawbar pull can potentially be employed for traversability prediction, traction control, and trajectory following which, in turn, improve overall performance of off-road wheeled vehicles. The proposed algorithm uses an approximated form of the wheel-terrain interaction model and the Generalized Newton Raphson method to identify terrain parameters in real-time. With few measurements of wheel slip, i, vehicle sinkage, z, and drawbar pull, DP, samples, the algorithm is capable of identifying all the soil parameters required to predict vehicle driving forces over an entire range of wheel slip. The algorithm is validated with experimental data from a wheel-terrain interaction test rig. The identified soil parameters are used to predict the drawbar pull with good accuracy. The technique presented in this paper can be applied to any vehicle with rigid wheels or deformable wheels with relatively high inflation pressure, to predict driving forces in unknown environments.
A Motion Planning Method for Omnidirectional Mobile Robot Based on the Anisotropic Characteristics
Authors: Leng Chuntao , Cao Qixin , Huang Yanwen
Published: March 2012

A more suitable motion planning method for an omni-directional mobile robot (OMR), an improved APF method (iAPF), is proposed in this paper by introducing the revolving factor into the artificial potential field (APF). Accordingly, the motion direction derived from traditional artificial potential field (tAPF) is regulated. The maximum velocity, maximum acceleration and energy consumption of the OMR moving in different directions are analyzed, based on the kinematic and dynamic constraints of an OMR, and the anisotropy of OMR is presented in this paper. Then the novel concept of an Anisotropic-Function is proposed to indicate the quality of motion in different directions, which can make a very favorable trade-off between time-optimality, stability and efficacy-optimality. In order to obtain the optimal motion, the path that the robot can take in order to avoid the obstacle safely and reach the goal in a shorter path is deduced. Finally, simulations and experiments are carried out to demonstrate that the motion resulting from the iAPF is high-speed, highly stable and highly efficient when compared to the tAPF.
An Active Fault-Tolerant Control Method Ofunmanned Underwater Vehicles with Continuous and Uncertain Faults
Authors: Zhu Daqi , Liu Qian , Yang Yongsheng
Published: March 2012

This paper introduces a novel thruster fault diagnosis and accommodation system for open-frame underwater vehicles with abrupt faults. The proposed system consists of two subsystems: a fault diagnosis subsystem and a fault accommodation sub-system. In the fault diagnosis subsystem a ICMAC(Improved Credit Assignment Cerebellar Model Articulation Controllers) neural network is used to realize the on-line fault identification and the weighting matrix computation. The fault accommodation subsystem uses a control algorithm based on weighted pseudo-inverse to find the solution of the control allocation problem. To illustrate the proposed method effective, simulation example, under multi-uncertain abrupt faults, is given in the paper.
Fusion of GPS, Compass, and Camera for Localization of an Intelligent Vehicle
Authors: Deelertpaiboon Chirdpong , Parnichkun Manukid
Published: March 2012

This paper proposes a fuzzy based sensor fusion algorithm for localization of an intelligent vehicle by correcting translational error of latitude and longitude in easily available maps such as Google Earth. Even though the chosen map possesses translational error, the proposed algorithm will automatically correct and compensate this error by using the integration of a Global Positioning System (GPS), a magnetic compass, and a CCD camera. To integrate these sensors, all the sensing data must be converted to the same reference. The GPS and the magnetic compass provide global data, whereas the camera provides local data. Since all sensors contain some uncertainties, the outputs of all sensors can be expressed by fuzzy numbers with triangular membership functions. All the fuzzy numbers are operated based on the alpha-cut closed interval properties. The proposed algorithm uses information from the GPS and the magnetic compass to calculate the global position of two selected pixels in two different segments, which represent road center line in the road images. Consequently, by knowing the global positions of the selected pixels, it is possible to calculate the horizontal and vertical deviations that the waypoints in the original map are to shift. The system performs efficiently on an unmarked road inside Asian Institute of Technology Thailand (AIT) campus.
Multi-Robot Searching using Game-Theory Based Approach
Authors: Meng Yan
Published: March 2012

This paper proposes a game-theory based approach in a multi–target searching using a multi-robot system in a dynamic environment. It is assumed that a rough priori probability map of the targets' distribution within the environment is given. To consider the interaction between the robots, a dynamic-programming equation is proposed to estimate the utility function for each robot. Based on this utility function, a cooperative nonzero-sum game is generated, where both pure Nash Equilibrium and mixed-strategy Equilibrium solutions are presented to achieve an optimal overall robot behaviors. A special consideration has been taken to improve the real-time performance of the game-theory based approach. Several mechanisms, such as event-driven discretization, one-step dynamic programming, and decision buffer, have been proposed to reduce the computational complexity. The main advantage of the algorithm lies in its real-time capabilities whilst being efficient and robust to dynamic environments.
Rapid Traversability Assessment in 2.5D Grid-based Map on Rough Terrain
Authors: Gu Jiajun , Cao Qixin , Huang Yi
Published: March 2012

This paper presents a rapid traversability assessment approach based on an extended 2.5D grid-based representaion of the rough terrain. Stereo vision system is used to perceive the environment surrounding robot. Conventional 2D, 3D and other 2.5D grid maps determine the traversability indices of the grids directly from the sensor feedback, while our approach attempts to address the indices of terrain from multiple grids instead. By analyzing the properties of multiple grids that the robot is to traverse, passable grids are distinguished, which also takes the robot's size into account. Fuzzy logic framework is applied to extract traversabiltiy indices from the terrain characteristics. A soccer robot equipped with a stereo vision system is adopted for experiments. The results show that our map is capable of speeding the process of traversability assessment and providing an autonomous mobile robot with a appropriate representation of 3D uneven terrain profile.
Behavior Selection Based Navigation and Obstacle Avoidance Approach Using Visual and Ultrasonic Sensory Information for Quadruped Robots
Authors: Izumi Kiyotaka , Habib Maki K. , Watanabe Keigo , Sato Ryoichi
Published: March 2012

A robot functioning in an environment may exhibit various forms of behavior emerge from the interaction with its environment through sense, control and plan activities. Hence, this paper introduces a behaviour selection based navigation and obstacle avoidance algorithm with effective method for adapting robotic behavior according to the environment conditions and the navigated terrain. The developed algorithm enable the robot to select the suitable behavior in real-time to avoid obstacles based on sensory information through visual and ultrasonic sensors utilizing the robot's ability to step over obstacles, and move between surfaces of different heights. In addition, it allows the robot to react in appropriate manner to the changing conditions either by fine-tuning of behaviors or by selecting different set of behaviors to increase the efficiency of the robot over time. The presented approach has been demonstrated on quadruped robot in several different experimental environments and the paper provides an analysis of its performance.
Evolution of Neuro-Controllers for Robots' Alignment using Local Communication
Authors: Gutiérrez Álvaro , Tuci Elio , Campo Alexandre
Published: March 2012

In this paper, we use artificial evolution to design homogeneous neural network controller for groups of robots required to align. Aligning refers to the process by which the robots managed to head towards a common arbitrary and autonomously chosen direction starting from initial randomly chosen orientations. The cooperative interactions among robots require local communications that are physically implemented using infrared signalling. We study the performance of the evolved controllers, both in simulation and in reality for different group sizes. In addition, we analyze the most successful communication strategy developed using artificial evolution.
Volumetric Calibration of Stereo Camera in Visual Servo Based Robot Control
Authors: Ulises Perez , Sohyung Cho , Shihab Asfour and
Published: March 2012

The primary objective of the paper is to propose a calibration method for a stereo camera used in a visual servo control for a robot manipulator. Specifically, projection matrix between the stereo camera and world coordinates is established using few calibration points and solved using the single value decomposition technique. Then calibration accuracy is compared for a randomized and designed set of points, and economical number of calibration points is recommended. Additionally, the non-linear lens distortion is modeled and corrected to improve the accuracy. In addition, this research focuses on the development and implementation of a fully automated visual servo control system using a stereo camera that is calibrated by proposed method.
The Improved SVM Multi Objects's Identification for the Uncalibrated Visual Servoing
Authors: Zeng Xiangjin , Huang Xinhan , Wang Min
Published: March 2012

For the assembly of multi micro objects in micromanipulation, the first task is to identify multi micro parts. We present an improved support vector machine algorithm, which employs invariant moments based edge extraction to obtain feature attribute and then presents a heuristic attribute reduction algorithm based on rough set's discernibility matrix to obtain attribute reduction, with using support vector machine to identify and classify the targets. The visual servoing is the second task. For avoiding the complicated calibration of intrinsic parameter of camera, We apply an improved broyden's method to estimate the image jacobian matrix online, which employs chebyshev polynomial to construct a cost function to approximate the optimization value, obtaining a fast convergence for online estimation. Last, a two DOF visual controller based fuzzy adaptive PD control law for micro-manipulation is presented. The experiments of micro-assembly of micro parts in microscopes confirm that the proposed methods are effective and feasible.
Stability Control for a Walking-Chair Robot with Human in the Loop
Authors: Tang Jiaoyan , Zhao Qunfei , Yang Ruqing
Published: March 2012

In this paper, a human-machine shared stability control strategy is proposed for a walking-chair robot with human in the loop. We consider the human in the loop as the torso of the robot and human movement as disturbance control to the system stability. Then the safe input regions for joints are given based on the zero moment point(ZMP) criterion. The control inputs to the system are defined according to the safe input regions. When the system state stays in the safe region, the control input select the human input. When the system state leaves the safe region, a safe control is determined according to the safe input set and the human input, which changes with the different system states. The control input is determined to be the combination of the human input and the safe control. Smooth transition from human input to snapped safe input is achieved so as to guarantee the rubust of the stabilitiy control. Simulation is done to analyze the influence of human input on system stability. The results show that the strategy increase the system stability with human in the loop.
Formations of Robotic Swarm: An Artificial Force Based Approach
Authors: Ekanayake Samitha W. , Pathirana Pubudu N.
Published: March 2012

Cooperative control of multiple mobile robots is an attractive and challenging problem which has drawn considerable attention in the recent past. This paper introduces a scalable decentralized control algorithm to navigate a group of mobile robots (swarm) into a predefined shape in 2D space. The proposed architecture uses artificial forces to control mobile agents into the shape and spread them inside the shape while avoiding inter-member collisions. The theoretical analysis of the swarm behavior describes the motion of the complete swarm and individual members in relevant situations. We use computer simulated case studies to verify the theoretical assertions and to demonstrate the robustness of the swarm under external disturbances such as death of agents, change of shape etc. Also the performance of the proposed distributed swarm control architecture was investigated in the presence of realistic implementation issues such as localization errors, communication range limitations, boundedness of forces etc.
Rudder Based Roll Control via Host-Computer of a Robotic Boat
Authors: Bao Xinping , Yu Zhenyu , Nonami Kenzo
Published: March 2012

Rudder based roll control of a small-sized robotic boat is a key technique for the devices on board to achieve good performance. This paper introduces a host-based robotic boat capable of performing basic movement operations. The course keeping and roll reduction are studied via rudder based method in simulations and sea trials. The boat dynamic model is built with the combination of mathematical analysis and system identification technique. A mixed sensitivity H∞ control method design is selected since yaw and roll motion are posed in different frequency domains. Computer simulations and experiments carried out show that successful results are achieved.
Quasi-Feature based Panoramic Video Creation for Multiview Object Tracking System
Authors: Park Changhan , Bae Kyung-Hoon
Published: March 2012

In this paper we present an efficient approach to building a panoramic video from mutiview cameras and to tracking objects. The proposed panoramic video creation module consists of two functions: (i) selecting four quasi-feature points in two adjacent frames acquired by corresponding multiple cameras and (ii) mosaicing the two images. Four pairs of selected quasi-feature points play a role of similarity reference in registering two adjacent frames. The mosaicing step uses the direct linear transformation (DLT) algorithm. The proposed tracking algorithm uses the active contour model (ASM), which is robust against partial occlusion. The proposed tracking module consists of four functions: (i) landmark point assignment, (ii) principal component analysis (PCA), (iii) modeling of local structure, and (iv) model fitting. While most conventional panoramic image creation methods are pixel-based, the proposed feature-based method provides more accurate tracking result. In the experiment, the created panoramic images exhibit high quality, which enables robust, real-time video tracking.
Correction Robot pose for SLAM based on Extended Kalman Filter in a Rough Surface Environment
Authors: Park Jaeyong , Lee Sukgyu , Park Joohyun
Published: March 2012

This research deals with mobile robot SLAM algorithm based on extended kalman filter. To enhance a accuracy of robot pose, one more extended kalman filter is used in a rough surface environment. The robot has uncertain kinematic model due to a caterpillar. When the robot drives on irregular surface, it's heading can be corrupted. We propose a method to correct uncertain robot pose using one more extended kalman filter through simulation results.
Genetic Programming Method of Evolving the Robotic Soccer Player Strategies with Ant Intelligence
Authors: Ramani R. Geetha , Subramanian R. , Viswanath P.
Published: March 2012

This paper presents the evolved soccer player strategies with ant-intelligence through genetic programming. To evolve the code for players we used the Evolutionary Computation tool (ECJ simulator-Evolutionary Compuation in Java). We tested the evolved player strategies with already existing teams in soccerbots of teambots. This paper presents brief information regarding learning methods and ant behaviors. Experimental results depicts the performance of the evolved player strategies.
Intelligent Robot-Assisted Humanitarian Search and Rescue System
Authors: Ko Albert W. Y. , Lau Henry Y. K.
Published: March 2012

The unprecedented scale and number of natural and man-made disasters in the past decade has urged international emergency search and rescue communities to seek for novel technology to enhance operation efficiency. Tele-operated search and rescue robots that can navigate deep into rubble to search for victims and to transfer critical field data back to the control console has gained much interest among emergency response institutions. In response to this need, a low-cost autonomous mini robot equipped with thermal sensor, accelerometer, sonar, pin-hole camera, microphone, ultra-bright LED and wireless communication module is developed to study the control of a group of decentralized mini search and rescue robots. The robot can navigate autonomously between voids to look for living body heat and can send back audio and video information to allow the operator to determine if the found object is a living human. This paper introduces the design and control of a low-cost robotic search and rescue system based on an immuno control framework developed for controlling decentralized systems. Design and development of the physical prototype and the immunity-based control system are described in this paper.