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The next generation of service robots capable of such sophisticated services as errands, table/room settings, etc. should have in itself a database of a large number of object instances human use daily. However, it may be impractical, if not impossible, that human should construct such a database for robots and update it each time new objects are introduced. To reduce the level of human involvement to a minimum, we propose a method for a robot to self-model the objects that are referred to or pointed out by human. The approach starts with the generic description of object categories assumed available a-priori. The generic description represents a category of objects as a geometric as well as functional integration of parts the 3D shape of which can be depicted as generalized cones or cylinders representing geometrical primitives or Geons. Given the 3D point clouds from the scene, 3D edge detection segments out the target object referred by human by removing out the background and/or neighboring objects. At the same time, it decomposes the target object into its parts for modeling. Here, we show that a rotational symmetric part or object, a special case of generalized cylinder, can be modeled precisely with only partial 3D point cloud data available. The proposed approach based on the generic description of object categories allows the self-modeling to infer a modeling procedure, estimate a full model from partial data, and inherit functional descriptions associated with parts. Experimental results demonstrate the effectiveness of proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents preliminary results of a textureless object recognition system for an indoor mobile robot. Our approach relies on 1) segmented linear features, and 2) pairwise geometric relationships between features. This approach is motivated by the need for recognition strategies that can handle many of indoor objects that have no little or not textural information on their surfaces, but have strong geometrical consistency within the same object class. Our matching method consists of two steps. First, we find correspondence candidates between linear fragments. Second, a spectral matching algorithm is used to find the subset of correspondences which is the most consistent. Both matching methods are learnt by using logistic classifiers. We evaluated the developed recognition system with our own database, which is composed of eight indoor object classes. We also compared the performance of our line feature based recognition approach with a SIFT feature based method. Experimentally, it turned out that the line features are superior in our problem setup - the detection of textureless objects. [ABSTRACT FROM AUTHOR]

In this paper a visual servoing architecture based on a parallel robot for the tracking of faster moving objects with unknown trajectories is proposed. The control strategy is based on the prediction of the future position and velocity of the moving object. The synthesis of the predictive control law is based on the compensation of the delay introduced by the vision system. Demonstrating by experiments, the high-speed parallel robot system has good performance in the implementation of visual control strategies with high temporary requirements. [ABSTRACT FROM AUTHOR]

A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. It attempts to challenge a long-standing problem in robot vision, so called, how to ensure the dependability of its performance under the large variation in visual properties of a scene due to changes in illumination, texture, occlusion, as well as camera pose. To ensure the dependability, we propose a behavioral process in vision, where possible interpretations are carried probabilistically in space and time for further investigations till they are converged to a credible decision by additional evidences. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences based on in-situ monitoring of environmental variations, 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences [ABSTRACT FROM AUTHOR]

This paper describes the software architecture of intelligent robots, developed by Center for Intelligent Robotics (CIR). The architecture employs a hybrid type consisting of deliberate, sequencing and reactive behaviors. The primary contributions of the architecture are the followings: 1) reusability and extensibility for the rapid development of robot systems with different requirements and 2) adaptability to distributed computing environments, different OS's and various programming languages. The architecture has successfully been applied to the development of CIR's many robot platforms such as T-Rot, Kibo and Easy Interaction Room. T-Rot and Kibo have been exhibited at the 2005 Asia-Pacific Economic Cooperation (APEC) in Korea. [ABSTRACT FROM AUTHOR]

Object recognitions are challenging tasks, especially partially or fully occluded object recognition in changing and unpredictable robot environments. We propose a novel approach to construct semantic contexts using ontology inference for mobile robots to recognize objects in real-world situations. By semantic contexts we mean characteristic information abstracted from robot sensors. In addition, ontology has been used for better recognizing objects using knowledge represented in the ontology where OWL (Web Ontology Language) has been used for representing object ontologies and contexts. We employ a four-layered robot-centered ontology schema to represent perception, model, context, and activity for intelligent robots. And, axiomatic rules have been used for generating semantic contexts using OWL ontologies. Experiments are successfully performed for recognizing partially occluded objects based on our ontology-based semantic context model without contradictions in real applications. [ABSTRACT FROM AUTHOR]

A highly flexible framework for visualization and sensor simulation in three-dimensional environments is presented. By allowing the insertion of freely programmable elements for online scene modification, a programmer can customize the framework to fulfill the exact simulation or visualization needs of an application of interest. Furthermore, the framework provides simple external interfaces so that multiple clients can be attached to it with ease. The frameworks' capabilities are demonstrated with two complex robotic applications that require both a high quality simulation of cameras and lasers scanners and an intuitive 3D visualization. [ABSTRACT FROM AUTHOR]

The ability to follow specific and task-relevant paths is an essential feature for legged humanoid robots. In this paper, we describe a technique for programming walking paths for humanoid robots based on imitation. Demonstrated paths are synthesized as NURBS (Non Uniform Rational B-Spline), and can be adapted by the robot based on local and dynamic information. We report simple experiments performed with a Robosapien V2 low-cost humanoid toy which has been suitably enhanced to support imitation-based programming. We show that despite robot limitations rather complex navigational tasks can be achieved through visual guidance. The system combines inputs from multiple sensory devices, including a motion tracker and a monocular vision system for landmark recognition. [ABSTRACT FROM AUTHOR]

Robots that work alongside people in their homes and workplaces could potentially extend the time an elderly person can live at home, provide physical assistance to a worker on an assembly line, or help with household chores. Human environments present special challenges for robot manipulation, since they are complex, dynamic, uncontrolled, and difficult to perceive reliably. For tasks that involve two handheld objects, the use of two arms can help overcome these challenges. With bimanual manipulation, a robot can simultaneously control two handheld objects in order to better perceive key features, control the objects with respect to one another, and interact with the user. [ABSTRACT FROM AUTHOR]

A new concept of a tactile human-machine interface for surgical interventions via multimodal computer navigated surgery is presented in this paper. In contrast to conventional computer navigated surgery, information about the surgeon are explicitly processed and used to augment the human machine interaction by a vibro-tactile display. By means of this display the system is extended by non visual data presentation through tactile information transmission. Different tactile activation schemes (mono linear, duo linear) in which different numbers of tactors are activated to transmit direction information, are tested and compared. The experimental evaluation adds up with a mean error of -0.35 mm and a standard deviation of 0.51 mm for the mono linear scheme and a mean error of -0.01 mm and a standard deviation of 0.62 mm for the duo linear scheme. [ABSTRACT FROM AUTHOR]

Hand posture understanding is essential to human robot interaction. The existing hand detection approaches using a Viola-Jones detector have two fundamental issues, the degraded performance due to background noise in training images and the in-plane rotation variant detection. In this paper, a hand posture recognition system using the discrete Adaboost learning algorithm with Lowe's scale invariant feature transform (SIFT) features is proposed to tackle these issues simultaneously. In addition, we apply a sharing feature concept to increase the accuracy of multi-class hand posture recognition. The experimental results demonstrate that the proposed approach successfully recognizes three hand posture classes and can deal with the background noise issues. Our detector is in-plane rotation invariant, and achieves satisfactory multi-view hand detection. [ABSTRACT FROM AUTHOR]

Research in mobile service robotics aims on development of intuitive speech interfaces for human-robot interaction. We see a service robot as a part of an intelligent environment and want to step forward discussing a concept where a robot does not only offer its own features via natural speech interaction but also becomes a transactive agent featuring other services' interfaces. The provided framework makes provisions for the dynamic registration of speech interfaces to allow a loosely-coupled flexible and scalable environment. An intelligent environment can evolve out of multimedia devices, home automation, communication, security, and emergency technology. These appliances offer typical wireless or stationary control interfaces. The number of different control paradigms and differently lay-outed control devices gives a certain border in usability. As speech interfaces offer a more natural way to interact intuitively with technology we propose to centralize a general speech engine on a robotic unit. This has two reasons: The acceptance to talk to a mobile unit is estimated to be higher rather than to talk to an ambient system where no communication partner is visible. Additionally the devices or functionalities to be controlled in most cases do not provide a speech interface but offer only proprietary access. [ABSTRACT FROM AUTHOR]

This paper presents a contribution to automatic model building in quadratic polynomial environments, in the context of programming by human demonstration. A human operator moves a demonstration tool equipped with a probe, in contact with an unknown environment. The motion of the demonstration tool is sensed with a 3D camera, and the interaction with the environment is sensed with a force/torque sensor. Both measurements are uncertain, and do not give direct information about the different objects in the environment (such as cylinders, spheres, planes,...) and their geometric parameters. This paper uses a Bayesian Sequential Monte Carlo method or particle filter, to recognize the different discrete objects that form the environment, and simultaneously estimate the continuous geometric parameters of these different quadratic polynomial objects. The result is a complete geometric model of an environment, with different quadratic polynomial objects at its building blocks. The approach has been verified using real world experimental data, in which it is able to recognize three different unknown quadratic polynomial objects, and estimate their geometric parameters. [ABSTRACT FROM AUTHOR]

We describe an approach to position estimation for mobile service robots and automatically guided vehicles which is based on RFID technology. The core idea of the approach is to structure the work space by means of a Smart Floor in a manner which enables and supports reliable navigation and positioning with absolute accuracy over large distances. The "intelligence" of the floor is in a dense, area-wide network of thousands of RFID transponder, which are mounted underneath the regular floor covering and quasi serve as radio beacons. The navigation system described in this paper, has been presented at CeBIT 2006 in Hannover by invitation of the German Ministry of Education and Research. InMach Intelligente Maschinen has further received the Walter Reis Innovation Award for Service Robotics for this innovative solution. [ABSTRACT FROM AUTHOR]

Local localization of a fully autonomous mobile robot in a partial map is an important aspect from the view point of accurate map building and safe path planning. The problem of correcting the location of a robot in a partial map worsens when sonar sensors are used. When a mobile robot is exploring the environment autonomously, it is rare to get the consistent pair of features or readings from two different positions using sonar sensors. So the approaches, which rely on readings or features matching, are prone to fail without exhaustive mathematical calculations of sonar modeling and environment modeling. This paper introduces link graph based robust two step feature chain based localization for achieving online SLAM (Simultaneous Localization And Mapping) using sonar data only. Instead of relying completely on matching of feature to feature or point to point, our approach finds possible associations between features to localize. The link graph based approach removes many false associations enhancing the SLAM process. We also map features onto Occupancy Grid (OG) framework taking advantage of its dense representation of the world. Combining features onto OG overcomes many of its limitations such as the independence assumption between cells and provides for better modeling of the sonar providing more accurate maps. [ABSTRACT FROM AUTHOR]

One of the main challenges in the field of robotics is to make robots ubiquitous. To intelligently interact with the world, such robots need to understand the environment and situations around them and react appropriately, they need context-awareness. But how to equip robots with capabilities of gathering and interpreting the necessary information for novel tasks through interaction with the environment and by providing some minimal knowledge in advance? This has been a longterm question and one of the main drives in the field of cognitive system development. The main idea behind the work presented in this paper is that the robot should, like a human infant, learn about objects by interacting with them, forming representations of the objects and their categories that are grounded in its embodiment. For this purpose, we study an early learning of object grasping process where the agent, based on a set of innate reflexes and knowledge about its embodiment. We stress out that this is not the work on grasping, it is a system that interacts with the environment based on relations of 3D visual features generated trough a stereo vision system. We show how geometry, appearance and spatial relations between the features can guide early reactive grasping which can later on be used in a more purposive manner when interacting with the environment. [ABSTRACT FROM AUTHOR]

This paper presents experiments in dynamic targets detection using panoramic images, which represent rich visual sources of global scenes around a robot. Moving targets (people) are distinguished as foreground pixels in binary images detected using a modified optical flow approach where the intensity of lighting source is variable. The directions of detected targets are determined using two strategies; the first one is convenient for unfolded panoramic images; it searches most probable regions in the last binary image by calculating a histogram of foreground pixels on its columns. The second approach is applied on raw panoramic images; it regroups foreground pixels using a technique that generates a new pixel's intensity depending on the intensities of its neighbors. [ABSTRACT FROM AUTHOR]

A paracatadioptric camera consists of the coupling of a parabolic mirror with a telecentric lens which realizes an orthographic projection to the image sensor. This type of camera provides large field of view images and has therefore potential applications for mobile and aerial robots. This paper is concerned with visual servoing using paracatadioptric cameras. A new optimal combination of visual features is proposed for visual servoing from spheres. Using this combination, a classical control law is proved to be globally stable even in the presence of modeling error. Experimental and simulation results validate the proposed theoretical results. [ABSTRACT FROM AUTHOR]

This paper proposes a switched visual feedback control method for a micro helicopter under occlusions. Two stationary cameras are placed on the ground. They track four black balls attached to rods connected to the bottom of the helicopter. The control input is computed by using the errors between the positions of the tracked objects and pre-specified reference values for them. The multi-camera configuration enables us to design a switched controller which is robust against occlusions. The proposed controller selects a camera which correctly measures all of the tracked object positions at each time. If a camera loses a tracked object, then the camera searches for the four tracked objects by using an image data captured from the other camera. The proposed controller can keep the helicopter in a stable hover even when one of the cameras loses tracked objects due to occlusions. [ABSTRACT FROM AUTHOR]

Object search is a very common task we perform each time we need an object. Humanoid robots are multipurpose platforms and will need to use generic tools to extend their capacities. It must thus be able to look for objects, to localize and use them. A search behavior would be a great improvement in humanoid autonomy and a step forward toward their rise outside laboratories. Before starting a search behavior, the robot needs a model of the desired object. This model could be provided by an external mechanism, but a humanoid has all the required abilities to build that model by its own. An undergoing project in our laboratory, called the "Treasure hunting" aim at integrating in a unique cycle, the model building of an unknown object, and the search for that object in an unknown environment. With such a combined skill, the robot may incrementally build a knowledge of its surrounding environment and the object it has to manipulate without any a-priori models. Latter the robot would be able to find and recognize that object. The time constraint is crucial, as a reasonable limit has to be set on the time an end user can wait the robot to achieve its mission. This paper will focus on the search behavior and we assume that the object model is already created. [ABSTRACT FROM AUTHOR]

This paper investigates the use of semantic information to link ground-level occupancy maps and aerial images. A ground-level semantic map is obtained by a mobile robot equipped with an omnidirectional camera, differential GPS and a laser range finder. The mobile robot uses a virtual sensor for building detection (based on omnidirectional images) to compute the ground-level semantic map, which indicates the probability of the cells being occupied by the wall of a building. These wall estimates from a ground perspective are then matched with edges detected in an aerial image. The result is used to direct a region- and boundary-based segmentation algorithm for building detection in the aerial image. This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile robot can explore the area by itself, giving the robot an ability to "see" around corners. At the same time, the approach can compensate for the absence of elevation data in segmentation of aerial images. Our experiments demonstrate that ground-level semantic information (wall estimates) allows to focus the segmentation of the aerial image to find buildings and produce a ground-level semantic map that covers a larger area than can be built using the onboard sensors. [ABSTRACT FROM AUTHOR]

Consider a large group of agents chasing a small group of moving targets. Assume each agent moves at constant speed toward the closest target. This paper studies the problem of controlling the agents indirectly by specifying the motion of the targets. In particular, it considers the problem of maintaining a minimum separation distance between each pair of agents, something that is impossible to do with only one target. This paper shows that only two targets are necessary to maintain separation between four agents. It also shows results in simulation to support the conjecture that only two targets are necessary to maintain separation between any number of agents, given suitable initial conditions. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid formation controller approach for non-holonomic mobile robots. This approach is based on the stable switching between a leader-following formation controller and an orientation controller. The switching attempts to maintain low values of formation errors during specific leader movements that otherwise will produce a significant increment on such errors. Experimental results on commercial unicycle-like mobile robots are provided to show the feasibility and performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper presents a novel tripedal mobile robot STriDER (Self-excited Tripedal Dynamic Experimental Robot) and considerations for gait planning strategies based on kinematics. To initiate a step, two of the robot's legs are oriented to push the center of gravity outside the support triangle formed by the three foot contact points, utilizing a unique abductor joint mechanism. As the robot begins to fall forward, the middle leg or swing leg, swings in between the two stance legs and catches the fall. Simultaneously, the body rotates 180 degrees around a body pivot line preventing the legs from tangling up. In the first version of STriDER the concept of passive dynamic locomotion was emphasized; however for the new version, STriDER 2.0, all joints are actively controlled for robustness. Several kinematic constraints are discussed as the robot takes a step including; stability, dynamics, body height, body twisting motion, and the swing leg's path. These guidelines will lay the foundation for future gait generation developments utilizing both the kinematics and dynamics of the system. [ABSTRACT FROM AUTHOR]

This paper presents a robust neural network motion tracking control methodology for piezoelectric actuation systems employed in micro/nano manipulation. This control methodology is proposed for tracking desired motion trajectories in the presence of unknown system parameters, non-linearities including the hysteresis effect, and external disturbances in the control systems. In this paper, the control methodology is established including the neural networks and a sliding scheme. In particular, the radial basis function neural networks are chosen in this study for function approximations. The stability of the closed-loop systems and convergence of the position and velocity tracking errors to zero are assured by the control methodology in the presence of the aforementioned conditions. Simulation results of the control methodology for tracking of a desired motion trajectory is presented. With the capability of motion tracking, the proposed control methodology can be utilised to realise high performance piezoelectric actuated micro/nano manipulation systems. [ABSTRACT FROM AUTHOR]

The paper presents T1R3-type fully-isotropic redundantly-actuated parallel manipulators (PMs) with four degrees of freedom. The mobile platform has one independent translation (T1) and three independent rotations (R3). A method is proposed for structural synthesis of fully-isotropic redundantly-actuated T1R3-type PMs based on the theory of linear transformations. A one-to-one correspondence exists between the actuated joint velocity space and the external velocity space of the moving platform. The Jacobian matrix mapping the two vector spaces of fully-isotropic T1R3- type PMs presented in this paper is 4×4 identity matrix throughout the entire workspace. The condition number and the determinant of the Jacobian matrix being equal to one, the manipulator performs very well with regard to force and motion transmission capabilities. Redundant actuation is used to obtain fully-isotropic solutions. As far as we are aware, this paper presents for the first time in the literature the use of redundancy to design fully-isotropic T1R3-type PMs. [ABSTRACT FROM AUTHOR]

Due to their compliance and high dexterity, biologically-inspired continuum robots have attracted much interest for applications such as medical surgery, urban search and rescue, de-mining etc. In this paper, we will present an application to medical surgery-colonoscopy by designing a pneumatic-driven flexible robotic manipulator, called ColoBot. The focus of this paper lies in the sensor-based guidance control of the ColoBot in a tubular, compliant and slippery environment of human colon. The kinematic model related the position and orientation of distal end of ColoBot to the actuator inputs is firstly developed and formulated for orientation control of ColoBot. For the autonomous guidance inside the colon, a method based on a circumscribed circle is utilized to calculate the real-time reference paths from the measurement of three sensors for orientation control of the Colobot. This proposed approach can be extended to the control of continuum robots in the conditions of a dynamically confined space. The experimental results on an emulation platform will be presented in order to validate the proposed control strategy. [ABSTRACT FROM AUTHOR]

A safe robot arm can be achieved by either a passive or active compliance system. A passive compliance system composed of purely mechanical elements often provide faster and more reliable responses for dynamic collision than an active one involving sensors and actuators. Since both positioning accuracy and collision safety are important, a robot arm should exhibit very low stiffness when subjected to a collision force greater than the one causing human injury, but maintain very high stiffness otherwise. To implement these requirements, a novel safe joint mechanism (SJM), which consists of linear springs and a slider-crank mechanism, is proposed in this research. The SJM has the advantages of variable stiffness which can be achieved only by passive mechanical elements. Various experiments of static and dynamic collisions showed the high stiffness of the SJM against an external force of less than the critical impact force, but an abrupt drop in the stiffness when the external force exceeds the critical force, thus guaranteeing collision safety. Furthermore, the critical impact force can be set to any value depending on the application. [ABSTRACT FROM AUTHOR]

In this paper, we present a face tracking and detection algorithm in real time camera input environment. To trace and extract a face image in complicated background and various illuminating conditions, we used pyramidal Lucas-Kanade feature tracker. Also we used KLT algorithm, which has robustness for rotated facial image, to extract the distinguishing feature of face area. [ABSTRACT FROM AUTHOR]

This paper introduces a novel mechanism for surgical robotic systems to generate human arm-like compliant motion. The mechanism is based on the idea of the equilibrium point control hypothesis which claims that multi-joint limb movements are achieved by shifting the limbs' equilibrium positions defined by neuromuscular activity. The equilibrium point control can be implemented on a robot manipulator by installing two actuators at each joint of the manipulator, one to control the joint position, and the other to control the joint stiffness. This double-actuator mechanism allows us to arbitrarily manipulate the stiffness (or impedance) of a robotic manipulator as well as its position. Also, the force at the end-effector can be estimated based on joint stiffness and joint angle changes without using force transducers. A two-link manipulator and a three-link manipulator with the double-actuator units have been developed, and experiments and simulation results show the potential of the proposed approach. By creating the human arm-like behavior, this mechanism can improve the performance of robot manipulators to execute stable and safe movement in surgical environments by using a simple control scheme. [ABSTRACT FROM AUTHOR]

The MPEG-7 texture description tools are applied to the retrieval of the historical aerial photographs. These aerial photographs had been digitized into gray-scaled and low-resolution images to build a digital library. The aerial image retrieval over the digital library is achieved on the basis of 1) texture feature extraction methods, which are homogeneous texture, texture browsing and edge histogram in the MPEG-7 texture descriptors, and 2) their corresponding similarity measurements. The image retrieval methods are evaluated over a collection of historical aerial photographs. The paper presents the retrieval results of these texture feature extraction methods. [ABSTRACT FROM AUTHOR]

Currently, there are many system requirements to guarantee the scalability, fault-tolerance, and high performance in the rapidly evolving research fields such as Grid and P2P technologies. Due to the dynamic nature of the Grid computing and P2P in networks, the behavior of system might be very unpredictable in respect of reliability. In this paper, we propose the Group Peer based P2P Grid system architecture with k-Redundancy SchemeThis research work has been supported by Grid Middleware Center, ITRC program of the Korea Ministry of Information and Communications. that can satisfy these requirements. With respect to load balancing, this P2P Grid system clearly shows that redundancy scheme of group peer guarantees the reliability for resource or service discovery. Through the theoretical analysis and simulation, we discuss the performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

It is very difficult to acquire high-fidelity flight test data for small airplanes such as typical unmanned aerial vehicles and RC airplanes because MEMS-type small sensors used in the tests do not present reliable data in general. Besides, it is not practical to conduct expensive flight tests for low-priced small airplanes in order to simulate their flight characteristics. A practical approach to obtain acceptable flight data, including stability and control derivatives and data of weights and balances, is proposed in this study. Aircraft design software such as Darcorp's AAA is used to generate aerodynamic data for small airplanes, and moments of inertia are calculated from CATIA, structural design software. These flight data from simulation software are evaluated subjectively and tailored using simulation flight by experienced pilots, based on the certified procedure in FAA AC 120-40B, which are prepared for manned airplane simulators. Use of design S/W for generation of parameter values representing flight characteristics turns out valid. In this study a practical procedural standard is established for procuring reliable data replicating flight characteristics of an airplane. [ABSTRACT FROM AUTHOR]

The paper introduces major technical specifications of the Line II railway simulators of Pusan City in Korea. Comparing design specifications of the railway simulators with those of the light aircraft Flight Training Device (FTD), the paper reveals commonality of implementation technologies applied to both simulators: Overall configurations and design philosophies are basically the same. In both programs VMEbus computing systems with UNIX are adopted as backbones of the simulators. It is found that the railway simulators are less stringent in real-time requirements than the aircraft FTD and the railway simulators are designed to be more event-driven and object-oriented. The experiences show that models may be diverse depending on the objects but implementation technologies are about the same. Maximizing portability of implementation technologies is a matter of an organization's strategy of adopting standardized processes and modular technologies available and most economic to them. [ABSTRACT FROM AUTHOR]

In multi-tasking real-time systems, inter-task cache interference due to preemptions degrades system performance and predictability, complicating system design and analysis. To address this problem, we propose a novel scheduling scheme, called LPS (Limited Preemptible Scheduling), that limits preemptions to predetermined points with small cache-related preemption costs. We also give an accompanying analysis method that determines the schedulability of a given task set under LPS. By limiting preemption points, the proposed LPS scheme reduces preemption costs and thus increases the system throughput. Experimental results show that LPS can increase schedulable utilization by more than 10 % and save processor time by up to 44 % as compared with a traditional fully preemptible scheduling scheme. [ABSTRACT FROM AUTHOR]