An implementation of a non-linear control scheme for hex rotors will be presented. The cascaded control scheme consisting of an attitude, a velocity and a position control level, empowers the hex rotor to be easily upgraded with more sophisticated behaviors. The attitude control utilizes the backstepping approach, which was introduced by Bouabdallah [1] for quad rotors, later improved and adapted to hex rotors by Arellano-Muro [2]. The implementation of the velocity and position controllers follow Voos [3]. Parameters, necessary for the model based control were identified numerically, with the help of direct measurement and by the use of flight experiment data and parameter estimation techniques. Validation of the controllers is done by analyzing real flight data, which was taken during outdoor flight experiments, testing both manual flight and position hold.

This work tackles the problem of pursuit-evasion games between two pursuing and one evading unmanned aerial vehicle. The solution of this problem is derived by introducing a hierarchical decomposition of the game. On a superordinate collaboration level, the pursuers choose their optimal behavioral strategy (i.e. pursue and herd) resulting in a three-player non-cooperative dynamic game which is solved in a subordinate level of the overall game. This structure enables an intelligent behavior change for the pursuers based on game-theoretical solution methods. Depending on the state of the game it has to be evaluated which behavioral strategy yields the best results for the pursuers within the regarded time horizon. It is shown, that the pursuer's outcome can be improved by using a superordinate cooperation between them. Furthermore, this application was implemented on a real quad-rotor system. In experiments the quad-rotor teamed-up with a software-emulated pursuer and it was shown that another software-emulated quad-rotor was caught. This framework provides a solution concept for all types of dynamic games with an arbitrary number of players and teams having a non-cooperative and cooperative nature. The hierarchical decomposition gives more flexibility and allows team members to co-ordinate their behavior and thus to maximize their outcome.

In this paper the problem of two-player pursuit-evasion games with unmanned aerial vehicles (UAVs) in a three-dimensional environment is solved. A game theoretic framework is presented, which enables the solution of dynamic games in discrete time based on dynamic programming. The UAV agents taking part in the pursuit-evasion game are two identical quad-rotors with the same non-linear state space model, while the evaders' absolute velocity is smaller than the pursuers'. The convergence of the pursuit-evasion game is shown in numerical simulations. Finally, the approach is simulated on an embedded computer and tested for real-time applicability. Hence, the implementation and real-time execution on a physical UAV system is feasible.

Experimental results for a handheld six degrees of freedom parallel robot with realtime position control and disturbance attenuation are presented. The robot's base is freely movable in space by a human operator, while the tool is position controlled and stabilized relatively to a reference coordinate system. The challenge is to decouple the tool as far as possible from the user involved arm tremor and unintended motions. The robot is equipped with a camera-based position and orientation tracking system, linear actuators, and a realtime control system. Kinematics, co-ordinate transforms and workspace limits are presented with its specifications. Experiments with sinusoidal stimuli on a test stand and during the handheld operation are discussed with respect of stabilizing performance and work-space violation. The resulting error bounds of less than 0.5 mm in the Cartesian position demonstrate that such a robot device has the potential to improve the classical manual surgical interventions. Further, the paper demonstrates the compliance of the user motion to the workspace provided by the robot.

In this paper three collision avoidance methods for an unmanned aerial vehicle (UAV) are tested and compared to one another. The quadrocopter dynamic model with attitude and velocity controller, a trajectory generator and a selection of collision avoidance approaches were implemented. The first collision avoidance method is based on a geometric approach which computes a direction of avoidance from the flight direction and simple geometric equations. The second technique uses virtual repulsive force fields causing the UAV to be repelled by obstacles. The last method is a grid-based online path re-planning algorithm with A* search that finds a collision free path during flight. Various flight scenarios were defined including static and dynamic obstacles.

In this work an identification approach for vertical take-off and landing unmanned aerial vehicles (UAV) in hovering flight is presented. The nonlinear dynamic model is driven from the first principles. The model is then linearized to obtain a linear state-space model presentation of thirteenth order. To identify the unknown parameters, the state-space model has been divided into subsystems. The parameters of the individual subsystems can be determined by applying a suitable identification method such as the prediction-error minimization (PEM) method. A sequential quadratic programming technique (SQP) was used to obtain feasible initial values of the parameters to be identified. Finally, the gained model of the UAV has been validated.

This paper represents the Lyapunov stability study for the wheeled mobile robot C3P based on a non-linear and complex mathematical model. The candidate Lyapunov function used in this work is extracted from the robot kinetic energy equation, which includes the robot dynamics and kinematics models. Such function contains uncontrolable and unpredicticable variables that yeild to very complicated and long analitical analysis. Therefore the analysis is done -part- analiticaly and numericaly in this work, which shows some stability uncertainty within the stable regions. The uncertain stability regions are considered as unstable regions generated by specified operating points. The effect of the control parameters values on overcoming such non-stable regions is presented for different operating points. Forced disturbances are applied on the robot in two different practical experiments. The practical results illustrate the stability study.

Hierarchical localization frameworks provide efficient means for localizing a robot topologically and geometrically. The metric localization performance is enhanced since the searchable space is confined to a previously identified topological place. This adapts well to large-scale environments. In this paper, a two-level hierarchical localization using a compact hybrid map is presented. The map preserves information set at two different abstractions and resolutions, and possesses both geometric and non-geometric properties. The coarse-resolution information enables global topological localization through place matching. The higher-resolution enables local metric localization through triangulation. The presented hierarchical localization is totally independent on the robot's motion model. For effectiveness in both mapping and localization, the map is constructed based on information-theoretic evaluation that selects only highly qualitative information. The approach is demonstrated using a vision sensor and the scale invariant feature transform.

In this paper, recent theoretical and experimental results in the area of structured intelligence research as well as future research directions and open questions are summarized. The Theory of Structured Intelligence (TSI) provides a transdisciplinary modular framework for intelligence research in psychology, neurosciences, computer science and engineering and can, thus, achieve synergetic effects and holistic results. The historical development of intelligence theories including strengths and weaknesses are traced. The TSI combines well-established theories and provides solutions to their shortcomings. Recent research results show the suitability of TSI in empirically validating human intelligence and implementing machine intelligence with application to path-planning of an autonomous robot. A description of work-in-progress, future directions and open questions namely in the fields “comparative static and dynamic test suite”, “functional and structural extensions and improvements”, “alternative functionally equivalent realizations of components”, and “further applications and impact of the TSI” are then elaborated.

Topological localization is a qualitative solution approach that can assist obtaining a faster quantitative metric solution by limiting the searchable space. Consequently, its efficiency is an essential requirement in hierarchical localization frameworks. This paper presents a topological map generation method with a localization scheme. Good compromise of performance measures - accuracy, memory and processing time - indicates the method's efficiency. The suggested implementations rely on information-theoretic selection of local features for node distinctive representation, and a visual codebook for compression. Testing the proposed approach on the COLD database, a recent specific benchmarking database for robotic topological mapping and localization, reveals its customization according to the vision sensor and environment characteristics. The approach guarantees over 90% localization accuracy with more than 50% overhead reduction, and is suitable for application in highly unstructured cluttered environments that are influenced by dynamics and illumination variations.

In this paper an off-grid hybrid energy system consisting of a reverse osmosis desalination plant for brackish water powered by renewable energy sources, and a diesel generator as back-up will be described. The whole system serves as a prototype for testing new automatic control methods to increase the plant reliability, which is crucial in remote arid areas. The necessary steps for the design of an optimal co-generation of both water and electricity such as the decision support system, modelling and simulation of the system and developing a fault tolerant control system will be depicted. The overall goal is to provide a cost optimal way to produce water and energy under the regional and technical boundary conditions. The presented work was performed within the framework of the European co-funded Project OPEN-GAIN.

Place recognition is a vital methodology for modeling environments and localizing autonomous mobile robots topologically. It can also be integrated in a hierarchical framework where it guides a fast and more precise metric position estimation. Especially for those hierarchical frameworks, it is crucial that the place recognition modules be highly accurate. In this paper, an information-theoretic approach that focuses on the efficiency of place recognition for topological environment modeling and localization is presented. The approach relies on a minimal discriminative feature set obtained from an entropy-based qualitative evaluation and a codebook compression. The generated environment feature map achieves a significant combination of high localization accuracy, speed and less memory storage.

In this paper, the collision avoidance behaviour in a recursive nested behaviour control structure for Unmanned Aerial Vehicles will be discussed. The architecture is an extension of the behaviour-based recursive control structure, which has been applied successfully to mobile robot applications. The system structure, as an abstraction of multiple cascaded control loops with feedback mechanisms, is robust against disturbances and model uncertainties. The obstacle awareness and collision avoidance are considered to be the most important issues in the field of Unmanned Aerial Vehicles (UAV), thus more attention will be paid to this topic. The collision avoidance utilizes a potential field method tailored for UAV application domain. The formulation of a repulsion forces based on radar sensor measurement is presented. The implementation of the collision avoidance system is also described.

Hierarchical localization provides both topological and quantitative metric solutions, with faster performance for the latter since the searchable space is minimized. The initial topological localization step is crucial in those frameworks and should be highly accurate. In this paper, a hierarchical localization approach that primarily focuses on the efficiency of the topological module is presented. The approach relies on a minimal set of qualitative entropy-based local features, which achieves both speed and localization accuracy. The abundant features are triangulated in a next step using a photogrammetric projective model to obtain a metric solution. The metric localization selects only the correct matches by regarding a simple yet efficient distance measure to overcome problems of data association and environment dynamics.

A generic system architecture for dependable interactive systems is proposed. The architecture is an extension of the behavior-based recursive control structure, which has already been applied successfully to robotic applications. The interaction between multiple robots or between a human user and robotic systems takes place on multiple behavioral levels providing fixed interfaces. A complex system is decomposed into levels according to the dynamics of behaviors and bandwidth of the interfaces. Signals from and to multimodal interface devices are processed according to the behavior-related information contents and fused within the behavior levels. The system structure, as an abstraction of multiple cascaded control loops with feedback mechanisms, is robust against disturbances and model uncertainties. The usage of the generic system architecture is demonstrated on the example of a semi-autonomous flying robot.

This paper introduces an approach for dynamically adapting the level of automation of a wheelchair system on the basis of the current level of the user's motor abilities. For this purpose, a study is described, during which participants drove through a course consisting of 14 sub-sections. The predictive validity of the participants' wheelchair driving behavior on their precision, tremor, wrist-finger velocity, arm-hand velocity and aiming capability was analyzed. The results demonstrate impressively (1) that some course sections can better be used in order to derive variables allowing a reasoning on the users' motor ability level than other sections and (2) that especially the precision ability can be predicted e.g. on the basis of the distances driven in the forward mode. Implications on how an adaptive assistance system for powered wheelchair could be implemented are discussed as is the impact of such a system on the wheelchair market.

A high level of psychomotor abilities often is essential for successfully operating many technical systems and especially medical and rehabilitation devices. This paper introduces an approach to enable a technical system to automatically assess its user's level of psychomotor abilities, so that it can adapt its level of automation and provide the user with more or less assistance depending on the individual user profile. For this purpose, a study has been conducted during which the motor abilities of the participants have been assessed and their wheelchair control behavior recorded. Bayesian networks (BN) and structural equation models (SEM) have been applied to model the relationships between the wheelchair control behavior and the motor abilities of the participants. The BN demonstrate usefulness and magnificent advantages compared to the SEM for modeling uncertainty in structure and parameter dependencies, which are shown by validation experiments. Although only a small amount of data samples (23 participants) was available for model generation, a target variable reflecting the user's precision ability was successfully classified based on real data input in more than 82% of cases.

The presented work is related to previous development of the holonomic wheeled mobile robot C3P. This paper focuses on the platform implementation and the kinematics/ dynamics solutions used for its position control structure. The platform prototype is proposed in detailed description concerning its construction and configuration. A controller based on feed forwarding the inverse dynamics torques with the inverse kinematics to overcome the platform singularities is proposed. The based controllers practical experiments results illustrate the position controller performance and its efficiency.

This work is a practical evaluation between two different holonomic wheeled mobile robot platforms. The evaluation criteria had been theoretically explained and used on the simulation level in previous publication. The main objective of this paper is evaluating each wheeled mobile robot practically using the proposed criteria. The first robot is the C3P, which has three caster wheels with wheel angular velocities actuation. The second robot is omni-directional wheeled platform with three omni-directional wheels. The inverse and forward kinematics required in the control structure is presented for the practical experiments, which illustrate the performance of each robot. The comparison is done with respect to three main aspects; 1) the mobility, 2) the total energy consumed by each robot in a finite interval of time, and 3) the hardware complexity. A cost functional is obtained to demonstrate the comparison, and a criteria is developed to measure the hardware complexity of each robot. The weight sum method enables the cost functional to show the importance of each aspect and to distinguish between the lowest cost platform with respect to each aspect importance.

In this paper, we present a new method to model individual cognitive abilities, which were originally described by structural equation models and which can be used to reduce the possibility of human error when interacting with complex technical system. Our proposed model is based on hierarchical Bayesian networks and deals therefore with uncertain and noisy data. The validity of the method is demonstrated on the basis of simulations of real-life data. The inference from the Bayesian network demonstrates that estimating the user's cognitive abilities is possible in a reliable manner in real-time. Structural and data dependency analyses further show that less evidence data are necessary to provide cognitive profile classification. This especially highlights the advantage of our new method in comparison to the - in psychology - traditionally used structural equation models. Such cognitive profiling will allow adapting a system's demand character to the cognitive ability level of an individual user, which will make operating that system less error-prone, as many human errors result out of systems requesting more cognitive abilities than the operator has available.

Especially for severely disabled people, a powered wheelchair is an important means to participate in societal life. To optimally support people in need without putting an additional burden on them, methods have been developed to enable controlling an electrically powered wheelchair on the basis of the user's natural gaze behavior. While existing approaches consider psychological/physiological research results, they do not take differences in the cognitive and motor abilities of the wheelchair users into consideration. However, according to the study at hand, which analyzed the gaze behavior of 10 wheelchair users when acting in an environment with a varying degree of familiarity, these individual differences are important when interpreting the gaze behavior for enhanced wheelchair control. Implications for a natural gaze-based assistance system for electrically powered wheelchairs are provided.

This paper proposes a novel method for planning point-to-point robot trajectories. With the new method, the requirement of an optimal path and the need of a slim motion due to the lack of free space can be compromised. The generated slim motion is suitable for applications where human-robot cooperation takes place. The new method is based on the synchronized links motion with a constant ratio of the link angle positions. The new method of synchronized motion was illustrated using a two-degree-of freedom (DOF) planar robot and compared with conventional methods.

In this paper, an appearance-based modeling of the environment is presented for the sake of mobile robot localization. The model allows perception and recognition within a topological context. Highly descriptive SIFT is used to extract local features from visual data acquired from an indoor environment. A method is developed to select those features, which are best for localization using a probabilistic modeling and an entropy measure. The impact of feature selection on the localization performance is more than 60% reduction in the storage and recognition time overhead. The methodology insures the recognition of different places with 96% precision, in spite of perceptual aliasing and image variability.

This paper presents a comparison between three different holonomic mobile robots. The first has three caster wheels with wheel angular velocities actuation and carries the name C3P. The second is omni-directional wheeled mobile robot and the third is a special holonomic robot configuration developed by ETH named Ramsis II. Inverse kinematic and forward dynamic models are presented for each robot for the simulation process. The simulation results illustrate the performance of each robot in comparison to the others. The comparison is done with respect to three main aspects; 1) the mobility, 2)the total energy consumed by each robot in a finite interval of time, and 3) the hardware complexity. A cost functional is obtained to demonstrate the comparison, and a criteria is developed to measure the hardware complexity of each robot. The weight sum method enables the cost functional to show the importance of each aspect and to distinguish between the lowest cost platform with respect to each aspect importance.

A dynamic model for the holonomic mobile robot C3P is proposed. The C3P has three caster wheels with angular velocities actuation. The model consists of two main dynamic equations which have been derived symbolically using a Lagrange approach. The first equation is the forward dynamics which is used to calculate the wheels angular velocities corresponding to the applied torques on the wheels. The second equation is the steering dynamic estimator for recursive calculation of the steering angles and their derivatives with respect to the wheel angular velocities and acceleration. The velocity control of the C3P using the dynamic model is simulated and compared to the kinematics based controller which have been proposed earlier. The simulation and experimental results clearly show the advantages of the dynamic model in relation to the kinematic one

Business processes show unpredictable and unstable behavior. This requires workflow systems to support monitoring functions with the ability to flexibly and robustly adapt to the changing activities of the workflow at runtime. In this paper flexible distributed realtime workflow monitoring is realized by a layered architecture. The architecture consists of: (1) middleware components supporting real-time and fault-tolerant monitoring and (2) different controllers for controlling workflows and performance data, view models for the specification of the graphical user interface and quality of service (QoS) requirements. A software system was implemented as a client-server application in Java using real-time and fault-tolerant CORBA middleware components. The prototype shows that the separation of process models, data models and view models can lead to flexible monitoring of workflows in real-time and thus guarantees robust and valuable information about business processes at runtime.

A "sophisticated" behaviour of an autonomous mobile robot is composed of several "primitive" behaviours. This is achieved using the so called "behaviour-networks". These circuits are built out of fuzzy gates defined to perform binary and unary operations. Two classes of binary operations are defined over the set S=X/spl times/Y, x/spl isin/[x/sub max/,-x/sub max/], y/spl isin/[y/sub max/,-y/sub max/], x,y/spl isin/R. The first class contains symmetric operations and is similar, in a certain sense, to the logical OR, AND and XOR. The second class includes asymmetric prevalence operations. Unary operations such as clipping and extending are also defined for conditioning the signal prior to the application of the binary operations. Although the main motivation for the development of these "fuzzy gates" was behaviour-fusion of mobile robots, they can be used as universal circuit elements for fuzzy-logic operations. An example shows a mobile robot with several primitive behaviours trying to reach a goal position whilst avoiding collision with an obstacle.>

The authors describe a method for mobile robot localization in an a priori known structured environment cluttered with unknown obstacles. The method is nearly independent of the number of obstacles encountered. An environment model based on ultrasonic range readings was built and compared with the reference model using clustering techniques. The method is very robust and works well if only a few parts of the environment are known. Results from an implementation on the mobile robot RAMSIS are presented.>

A generalized control structure for shaping the behavior of a mobile robot is described. The proposed structure possesses many desirable properties such as recursiveness, nestedness of the behavior bandwidth, and predefined interface of the behavior levels. It uses different system representations at the different levels of abstraction. A general formal description and the block-diagram realization of the different levels are given. The realization of several levels has been successfully validated on a mobile robot under realistic environmental conditions.>

The collision avoidance behavior in a recursive nested control structure design is discussed. A formulation of a repulsion force based on measurements of ultrasonic range and tactile force and moment is given. The avoidance behavior adapts to the dynamics of the mobile robot. The realization details emphasize the importance of keeping the system bandwidth as large as possible to increase the reflexiveness of the avoidance behavior. Real-world experiments confirm the effectiveness and robustness of the proposed procedure.>

A solution to the path-planning problem for mobile robots is proposed. The solution is based on a geometrical model, a logical model, and an associative memory. The geometrical modeling is done by a graph produced by analog-mapping preference gangways in the environment. The path search is made by a best-first algorithm in the logical model. The costs of the individual graph arcs are dynamically updated. During the search, the associative memory is repeatedly consulted for an available path. When a valid path is found it is learned by the memory for later use. For the memory, the path is tristate-encoded and preprocessed by the graph connection matrix. An example is given to illustrate the operation of the associative memory.>