In this work, a novel environment representation method which facilitates path planning for biped walking robots is presented. The robot's environment is represented by a 2D map consisting of free regions, obstacle regions and feasible paths over the obstacle regions. In the free regions, standard path planning methods can be applied to plan paths around large obstacles. These paths are combined with paths over obstacle regions which include stepping over small obstacles as well as changing the walking level. Search for feasible paths rests upon the approximation of the robot by a set of hulls whose shapes allow efficient checking of the path feasibility. By considering only a restricted set of paths over obstacles, some generality is traded against better time performance.

The paper outlines a novel approach for performing explosive ordnance disposal by use of a bimanual haptic telepresence system. This system enables an operator to perceive multimodal feedback from a remote environment for proper task execution. The developed experimental setup, comprising a bimanual human system interface and the corresponding bimanual teleoperator for use of both hands, is presented in detail. The teleoperation control architecture is discussed as well as a local model-based impedance control algorithm for manipulator control. Human-system performance is improved by means of stereo visualization of the tele-environment together with overlayed Augmented Reality assistance, and an algorithm for avoidance of dangerous manipulator configurations supported by augmented force feedback. Furthermore, a recently developed UDP communication library is presented for system interconnection taking into account compression of haptic data. Thus efficient and low delay of data transfer is ensured. The usability and effectiveness of the developed bimanual telepresence system are demonstrated by focusing a relevant task scenario, such as demining operations in a remote environment.

As a novel approach to force-reflecting teleoperation of a mobile teleoperator (MTO), a mobile haptic interface (MHI) is presented. The MHI actively follows the locomotion of an operator, who is no longer bound to be stationary during interaction with a remote environment. Thus, operator locomotion can be used as input for locomotion control of the MTO while keeping the advantage of force-reflection. The paper introduces a new paradigm for the position control of a nonholonomic platform and a new approach for the coupling of display and teleoperator in a teleoperation setup.

A new control scheme for uncalibrated robotic visual tracking problem is proposed that compromises the computational expenses of overall system with offline modeling and online control. A nonlinear visual mapping model for the uncalibrated hand-eye coordination is first proposed with an artificial neural network implementation. An online visual tracking controller is then developed together with a real-time motion planner. To improve the system performance, the control scheme is also integrated with a feedforward controller to compensate unknown object motions. Extensive simulations and experiments demonstrate the effectiveness of the proposed control scheme.

This paper presents a systematic approach to generate walking primitive databases for anthropomorphic 3D-bipeds allowing step length adaptation, direction changes and stepping over obstacles. The individual walking primitives are derived by optimal control techniques. Zero moment point (ZMP) and friction conditions at the feet ensuring postural stability of the biped, as well as bounds on the joint angles and on the control torques, are treated as constraints. The resulting reference trajectories are validated by dynamic simulations.

This article presents a novel gaze control strategy for obstacle avoidance in the context of vision guided humanoid walking. The generic strategy is based on the maximization of the predicted visual information. For information/uncertainty management a new hybrid formulation of an extended Kalman filter is employed. The performance resulting from this view direction control scheme shows the dependence of the intelligent gazing behavior on the pre-planned local path.

This article deals with specific aspects concerning the visual perception process of a humanoid walking machine. An active vision system provides the information about the environment necessary for autonomous goal-oriented locomotion. Due to errors in each stage of the perception process, ideal environment reconstruction is not possible. By modeling these errors, stochastic components can be compensated using a hybrid extended Kalman filter approach with an alternating reference frame, thus reflecting the discontinuous character of biped walking.. The perception results improved by filtering can be used for the autonomous locomotion of the robot. Experiments with the walking machine BARt-UH demonstrate the validity of our approach.

A multimodal Internet-based telepresence system with interactive stereo vision, additional photo-realistic predictive display, and kinesthetic bilateral coupling in three degrees of freedom is presented. For easy coupling of various telepresence components by a unified interface structure and a generic link management protocol a CORBA based interconnection framework has been developed. By solving a peg-in-hole task in an industrial environment and with varying communication delay times, the system provides all capabilities for multimodal telepresent remote maintenance and assembly.

Tactile array displays provide the Human Operator (HO) of a telepresence or Virtual Environment (VE) system with detailed tactile shape information on his/her fingertips. In previous work, an ideal specification profile for tactile array displays has been derived from human physiology and the biomechanics of human touch. Existing hardware developments still have tremendous shortcomings compared to such a specification profile. However, evaluation strategies have too often neglected the specificity of the particular application: in many application classes tactile display quality is mainly characterized by a subset of specification parameters, while other parameters play a rather subsidiary role. This paper suggests an application-specific evaluation approach associating the display quality of certain scenario properties under certain task conditions with corresponding hardware specification parameters. Results can help to design future tactile actuator arrays providing application-optimized display performance. The evaluation approach is exemplified by an experimental investigation of the spatial pin resolution of tactile array displays. Experiments were based on four separate tactile actuator systems driven in eight different resolution configurations.

Goal-oriented vision-guided biped locomotion requires a high degree of coordination between perception and walking. How to establish this coordination remains a fundamental and rarely studied problem in legged robotics. Some of our investigations into this field are outlined in this article by presenting recent results in vision-guided biped locomotion. The guidance and control approaches developed are experimentally validated on the biped robot BARt-UH. It is shown how perception techniques are employed in closed-loop for step sequence adaptation and locomotion control of a walking machine.

This article deals with the information management for active gaze control in the context of vision-guided humanoid walking. The proposed biologically inspired predictive gaze control strategy is based on the maximization of visual information. The quantification of the information requires a stochastic model of both, the robot and perception system. The information/uncertainty management, i.e. relationships between the system, state estimation and the active measurements, employs a coupled (considering cross-covariances) hybrid (reflecting the discontinuous character of biped walking) extended (copes with nonlinear systems) Kalman filter approach.

This paper presents an approach to fast object manipulation by dextrous re-grasping of multi-fingered hands. The approach is based on a real-time grasping force optimization (GFO) algorithm and a fingertip impedance control scheme. Both the controller and the GFO make use of 6D contact force sensor data at run-time. The latter keeps the contact forces as small as possible while considering friction limits at the contact points during (re)grasping. The impedance controller is used to impose the optimized contact forces onto the grasped object while simultaneously enabling active control of the fingertip positions. Experiments demonstrate the robustness of the approach and the increase in task speed during multi-fingered manipulation.

Free navigating robots are applied to increasingly complex tasks in both the industrial and service sectors. With task complexity rising, the likelihood of unexpected events is increasing. Advanced service robots therefore require intelligent controllers to handle task oriented exceptions, to select appropriate countermeasures and to execute these efficiently. In order to manage and to perform appropriately and to handle cascaded exceptions as well, systematic knowledge gathering, analysis and representation is required Here relational data models are extensively used to generate measures in case of external or internal exceptions, and to accept and store new information for use in similar situations. A hierarchical controller architecture that has been developed and verified using Petri net models, supervises planned task execution and enforces the measures required for successful autonomous operation. The efficiency of the proposed exception handling approach has been tested and evaluated with the mobile robot MACROBE performing several inspection and transportation tasks in a shop floor environment.

This paper presents the theoretical background and the implementation of a real-time interactive stereo vision system including vergence control. The vision system enables human operators to actively observe a remote real environment and allows high-fidelity visual sensing, useful in multimodal telepresence and teleaction tasks. The use of Internet protocol (IP) communication technology facilitates the application of the system in most wide area communication infrastructures. Evaluation experiments demonstrate the benefits of interactive stereo vision with respect to improved human task performance.

Human-system-interfaces for haptic display with emphasis on tactile information are research fields of growing interest. Their application to system design in multi-modal telepresence and virtual environment (VE) systems implies mechatronics engineering challenges as well as the need for consideration of human factors. A tactile actuator array for dynamic display of distributed tactile shape information is presented. Actuator design focus was directed at high pin forces and a bandwidth sufficient for most one-fingered tactile shape exploration tasks performed by dynamic interaction. The resulting overall device dimensions currently prohibit an attachment to the effector of typical kinesthetic feedback devices. Experimental results are presented for a virtual presence scenario where tactile stimulation emerges from dynamic interaction between virtual objects on a conveyer belt moving relative to a resting fingertip.

Presents a combined system for hand and finger kinesthetic feedback for the exploration and manipulation of different kinds of rigid objects in virtual environments. A three-degrees-of-freedom haptic interface, called DeKiFeD3 (Desktop Kinesthetic Feedback Device 3), with the capability of generating kinesthetic hand feedback, is combined with a commercial haptic glove to generate additional kinesthetic feedback to the fingers of a human operator. This system results in a new quality of kinesthetic perception and needs appropriate rendering algorithms, as described in this paper. The paper also presents an approach to improve the operator's immersion into a virtual scenario by adding auditory and visual feedback.

Introduces a modular all-in-one wheel system for combined steering/driving applied to service robots operating in indoor environments like homes, offices, or hospitals. The wheel system is based on standard tires, builds very compact, and provides a high pay load to dead load ratio. It is used as a building block to construct a wide variety of highly maneuverable mobile robots ranging from simple tricycles to fully holonomic locomotion platforms. Integration is simple, because each wheel system is equipped with the necessary control and communication infrastructure based on standard PC components.

Display of information to the operator in advanced physical and virtual telepresence systems has to comprise different modalities of human perception. Especially concerning the haptic modalities, model-based generation of appropriate stimuli to the operator is an important task. For this reason future research in telepresence and virtual reality requires a mathematical model of human perception due to external stimuli produced by feedback devices in a multi-modal telepresence system. The paper presents a mathematical framework for describing the principles of human perception in the terminology of systems theory. Formal descriptions of experiments performed in a virtual environment show the viability and advantage from the presented approach.

We present an approach to compensate for discrete contact state errors in regrasping tasks with multi-fingered robotic hands. An adaptation of reference trajectories connected with a hybrid discrete continuous control architecture allows stable grasps even if moving fingers cannot contact at the desired position on a grasped object. We propose a robust control setup that allows multiple regrasping tasks of objects to be performed using this compensation strategy and contact force optimization. Experimental results with the hydraulic robotic hand of the TUM verify the proposed approach and illustrate the increase in robustness for multi-fingered manipulation.

We present a distributed PC-based multimodal (haptic, visual and acoustic) telepresence and virtual presence system. Two desktop kinesthetic devices (DeKiFeD3 and DeKiTop3) with 3 degrees-of-freedom have been developed for multi-modal telepresence. Feedback to the human modalities of the visual, auditory, kinesthetic, tactile and temperature senses is generated using appropriate actuator hardware. We present several applications in virtual presence and teleoperation in physical remote environments.

We present the two-dimensional (2-D) version of the symmetries and perturbation model (SPmodel), a probabilistic representation model and an extended Kalman filter integration mechanism for uncertain geometric information that is suitable for sensor fusion and integration in multisensor systems. We apply the SPmodel to the problem of location estimation in indoor mobile robotics, experimenting with the mobile robot MACROBE. We have chosen two types of complementary sensory information: (1) range images; (2) intensity images; obtained from a laser sensor. Results of these experiments show that fusing simple and computationally inexpensive sensory information can allow a mobile robot to precisely locate itself. They also demonstrate the generality of the proposed fusion and integration mechanism.

In this paper a switching control strategy for robust stabilization of the 2nd-order nonholonomic 2-DOF SCARA robot R2D1 is presented. The first joint is actuated by a direct drive motor, whereas the second joint is equipped with a brake. The unactuated second joint is controlled by non-collocated linearization and a PD-controller. A stability region is derived and robustness is achieved by exploiting the contractive character of the perturbed stability region. The proposed switching control strategy assures global and robust position control of the second joint. Experimental results confirm the efficiency of the proposed approach.

This paper presents an information processing scheme which increases the autonomy of floor caring robots in indoor applications, such as cleaning or inspection of industrial and public floor areas. An automatic planner generates a serpentine path pattern by repeated and appropriate concatenation of up to five basic motion macros. This nominal path is executed by a Cartesian motion controller. In case of unexpected obstacles the robot updates its internal geometric representation of the work area to be processed and replans its path. Due to obstacle avoidance, certain areas may remain unprocessed. Location and topology of such areas are automatically reconstructed for repeated follow-up floor caring in case of temporary obstacles. For this purpose connecting maneuvres and paths of complete floor coverage are incrementally planned and executed. Landmark localization at automatically preplanned reference points allows online modification of motion commands and guarantees precise long distance path tracking. Feasibility of the developed techniques has been demonstrated in various long-term experiments with the prototype mobile service robot MACROBE.

Appearance-based 3D object recognition is becoming popular for the recognition of faces and unstructured objects in new applications, such as mobile service robots in health care environments. Typical recognition problems are a cluttered background, the need of real-time recognition for in-the-loop applications, like object recognition and grasping by a robot, and a large search area, often the full camera image. In our approach a search window is shifted across the image in a way similar to cross-correlation and after each shift the content of the search window is classified by use of a template tree. To achieve real-time capability, adaptation of template resolution and step-size between consecutive search windows are integrated within the tree structure. The robustness of the tree classifier is significantly increased by optimization of the classifiers within the tree nodes by use of information theory methods.

This article presents a novel approach to conflict-resolution for multiple mobile robots. By use of online motion planning, a framework for negotiation is developed, which permits quick decentralized and parallel decision-making. The key objective of the negotiation procedure is dynamic assignment of robot motion priorities. Thus, robots involved in a local conflict situation cooperate in planning and execution of the lowest cost motion paths without application of any centralized components. The features required for individual and cooperative motion are embedded in a hybrid control architecture. Results obtained from realistic simulation of a multirobot environment and also from experiments performed with two mobile robots demonstrate the flexibility and the efficiency of the proposed method.

The work presented in this paper is aimed at evaluating the influence of correlations between map entities on the process of robot relocation and global map building of the environment of a mobile robot navigating in an indoor environment. An EKF filter approach, supported by a probabilistic model to represent uncertain geometric information, is used to process the information obtained by the sensors mounted on the robot. We have developed two approaches, first, considering the existence of correlations, and second assuming independence between entities of the map. We have experimented with the mobile robot MACROBE, using its laser rangefinder.

The paper describes design issues of a mobile service robot for health care applications and domestic automation. Key components required for achieving semi-autonomous operation are surveyed, including: 1. a highly maneuverable locomotion platform, 2. an anthropomorphous manipulator, 3. a reliable multisensor system, and a 4. multimodal human-robot-interface. In addition, related information processing and control methodologies are presented. Special emphasis is put on a system architecture for integration of the individual components into a full-size service robot. Performance and usefulness of the proposed approaches are demonstrated through experiments in various real-world service scenarios.

An efficient noniterative algorithm for active localization of objects is developed. It is based on intersecting elliptic curves defined by uncertain range-sum measurements between a signal source, the objects, and a number of arbitrarily located receivers. Measurement errors are modelled as being unknown but bounded in amplitude by a closed convex set. Based on this set-theoretic uncertainty model, an error propagation analysis is performed, that allows one to accurately bound estimation errors. For discriminating object primitives and for discarding erroneous measurements, a hypothesis test is derived. The algorithm's computational load is much lower than for grid-based methods and iterative techniques. A recursive formulation is provided to support real-time applications.

Considers state estimation based on observations which are simultaneously corrupted by a deterministic amplitude-bounded unknown bias and a possibly unbounded random process. This problem is solved by developing a combined set theoretic and Bayesian recursive estimator. It provides a continuous transition between both concepts in that it converges to a set theoretic estimator when the stochastic error vanishes and to a Bayesian estimator when the deterministic error vanishes. In the mixed noise case, the new estimator supplies solution sets defined by bounds that are uncertain in a statistical sense.

We study the problem of localizing a mobile robot with an onboard-device making angular measurements on the location of known but indistinguishable landmarks. Novel algorithms are proposed for: 1) efficient posture initialization based on a simple linear solution; and 2) recursive posture estimation. Derived in a set theoretic framework, the algorithms cope with non-white, non-Gaussian noise and deterministic errors. Experiments with the set theoretic posture estimator demonstrate its simplicity and effectiveness in real-world applications.

Presents the 2D version of the symmetries and perturbation model (SPmodel), a probabilistic representation model and an EKF integration mechanism for uncertain geometric information that is suitable for sensor fusion and integration in multisensor systems. The authors apply the SPmodel to the problem of location estimation in mobile robotics, experimenting with the mobile robot MACROBE. The authors have chosen two types of sensorial information whose complementary nature allows a mobile robot to localize itself precisely in a known environment: range images and intensity images obtained from a laser sensor. By measuring distance to objects, range basically provides position information. On the other hand, the intensity image provided by the laser sensor (equivalent to a monocular vision system) can be used to detect vertical edges, corresponding to corners, frames, etc., which mainly provide angular information. Results of these experiments show that fusing simple and computationally inexpensive sensorial information can allow a mobile robot to precisely locate itself. They also demonstrate the generality of the proposed fusion and integration mechanism.

Intelligent human behaviour models can serve as a basis for semi-autonomous mobile robot systems. In this paper the necessity of hierarchical supervisory control for service task solution using a human-robot-interface (MRI) is motivated. The demands on information exchange between operator, MRI and service robot are outlined and categorised. A distributed planner to control the robot system is presented, enabling both flexible robot behaviour and online operator support. Effectiveness of the approach is demonstrated by experimental results achieved with the proposed MRI and the service robot ROMAN.

This article presents a novel approach to decentralized motion planning and conflict-resolution for multiple mobile robots. The proposed multirobot motion planning is an online operation, based on cost wave propagation within a discretized configuration space-time. By use of the planning method a framework for negotiation is developed, which permits quick decentralized and parallel decision-making. The key objective of the negotiation procedure is dynamic assignment of robot motion priorities. Thus, robots involved in a local conflict situation cooperate in planning and execution of the lowest cost motion paths without application of any centralized components. The features required for individual and cooperative motion are embedded in a hybrid control architecture. Results obtained from realistic simulation of a multirobot environment and also from experiments performed with two mobile robots demonstrate the flexibility and the efficiency of the proposed method.

We propose a novel approach to reference behavior specification for multiple robotic mechanisms using hybrid system models. Hybrid automata can specify discrete states (operational modes) and continuous variable reference values in one unified framework. An example mechanism with 3 degrees-of-freedom and a 6-legged walking machine with a combination of several hybrid automata for reference generation and synchronization are discussed. Simulation results show that a hybrid system model is an effective method for robotic behavior specification. Using a model verification tool we show that behavior correctness verification and parametric analysis are possible.

This article describes the localization system of a free-navigating mobile robot. Absolute position and orientation of the vehicle are determined by matching vertical planar surfaces extracted from a 3D-laser-range-image with corresponding surfaces predicted from a 3D-environmental model. Continuous localization is achieved by fusing single-image localization and dead-reckoning data by means of a statistical uncertainty evolution technique. Extensive closed-loop experiments with the full-scale mobile robot MAC-ROBE proved robustness, accuracy and real-time capability of this localization scheme.

This paper presents a real time approach for the integrated planning and execution of robot motion paths. Path planning is based on a virtual unsteady diffusion process, which is simulated online in a grid-based world model. This approach provides an elegant method of combining map-based and sensor-based planning operations. Necessary extensions of the basic procedure are introduced in order to adapt the planner to different types of mobile robots. An environmental representation using multiresolutional maps allows an efficient combination of local and global aspects of motion planning. A fast integrated cycle of sensing, planning and path execution enables the robot to react rapidly to environmental changes. Experiments performed with the mobile robot MACROBE demonstrate the simplicity and effectiveness of this approach.>

A new type of actively sensing multisonar system for obstacle avoidance, localization and map updating in indoor environments has been developed. It is composed of 24 individual intelligent transmitter and receiver elements arranged on a horizontal plane around a fast motion platform. The physical sensor elements can be electronically configured for various types of task-directed and situation-adaptive virtual sensor arrays, for example, reliable measurement of wall orientation and distance or for tracking a walking person. The combination of virtual sensor data with a priori information about the mission and the environmental situation permits the sensor system to keep up with the data rate requirements of fast mobile platforms. Experimental tests with the developed multisonar system demonstrate its improved perception capabilities compared to the state-of-the-art.>

In the past mobile robot research was often focused on various kinds of point-to-point transportation tasks. Mobile robot application in service tasks, however, requires quite different path planning and guidance approaches. This paper introduces and discusses in detail specific planning and guidance techniques for a mobile floor-cleaning robot. A kinematic and geometric model of the robot and the cleaning units as well as a 2D-map of the indoor environment are used for planning an appropriate cleaning path. The path is represented by a concatenation of two kinds of typical motion patterns. Each pattern is defined by a sequence of discrete cartesian intermediate goal frames. These frames represent position and orientation of the vehicle and must be translated into motion commands for the robot. The steps of this semi-automatic path planning system are illustrated by a typical cleaning environment. Vehicle guidance includes execution of the planned motion commands, estimation of the robot location, path tracking, as well as detection of and reaction to (isolated) obstacles. For location estimation a least-squares fitting of corresponding geometric contours from the 2D-environment map and geometric 2D-sensor data is used. Obstacle detection is accomplished by testing geometric 2D-sensor data to be part of the preplanned cleaning path. Path planning and parts of the developed vehicle guidance system have been tested with the experimental mobile robot MACROBE. Results reported in this paper demonstrate the efficiency of the described planning, location estimation and path tracking procedures in basic floor-cleaning tasks.>

This paper discusses a method for map and sensorbased planning and execution, i.e. navigation, of smooth collision-free robot motion paths. Application of an unsteady diffusion equation model to path planning in a time-varying world distinguishes this approach from prior work in the field. Collision-free robot paths between a start and a mission dependent goal point are generated very rapidly by on-line simulation of a diffusion process and by repetitively evaluating the gradient of the computed concentration distribution functions. Related numerical algorithms are appropriate for implementation on a massively parallel distributed processor architecture. This paper describes application of the approach to various scenarios of robot vehicle navigation. Results of a field experiment performed with the mobile robot MACROBE are presented.

A hierarchical optimization method based on the interaction prediction principle is applied to the freeway traffic control problem. The solution method is implemented on a multimicrocomputer system. Both analytical and experimental results concerning certain properties of the decentralized computation structure such as computation time, storage space, and communication requirements are presented.