This special issue - organized by the IEEE SMC TC on Distributed Intelligent Systems - targets recent research results, trends, and practical developments of distributed intelligent systems that accomplish advanced tasks in the industrial areas of manufacturing, power and energy, and logistics. Five high-quality contributions to this special issue have been selected in a strict peer review process supported by reputed international experts. Three submissions focus mainly on technical aspects related to the design, development and validation process of distributed, intelligent automation systems, whereas the other two papers treat application-related topics.

A rough mill is a manufacturing plant where lumber of approximate dimensions is cut into components of specific sizes, priorities, and qualities to fill customer orders for wood products such as furniture, doors, and window frames. Lumber is a valuable natural resource that is a significant expense to the company. By improving the processes in the rough mill, cost can be reduced and waste of natural materials is decreased. We present an overview of research in agent-based manufacturing systems. The operations in a rough mill are described and the decisions that operators take are identified. A rough mill decision support and simulation system is designed and implemented. An agent ontology for rough mill operations is developed. A prototype system is implemented to demonstrate the architecture and interagent communication. This prototype is extended to two lines of production and the negotiation protocol is presented. Extension of the approach to multiple lines of production is discussed. The prototype system is used to implement a decision support and simulation system that is validated with historical data. Finally, we present a comparison of the advantages and disadvantages of using the multiagent paradigm in rough mill decision support.

This paper presents an analytical approach to design a continuous time-invariant two-level control scheme for asymptotic stabilization of a desired period-one trajectory for a hybrid model describing walking by a planar biped robot with noninstantaneous double-support phase and point feet. It is assumed that the hybrid model consists of both single- and double-support phases. The design method is based on the concept of hybrid zero dynamics. At the first level, parameterized continuous within-stride controllers, including single- and double-support-phase controllers, are employed. These controllers create a family of 2-D finite-time attractive and invariant submanifolds on which the dynamics of the mechanical system is restricted. Moreover, since the mechanical system during the double-support phase is overactuated, the feedback law during this phase is designed to be minimum norm on the desired periodic orbit. At the second level, parameters of the within-stride controllers are updated by an event-based update law to achieve hybrid invariance, which results in a reduced-order hybrid model for walking. By these means, stability properties of the periodic orbit can be analyzed and modified by a restricted Poincaré return map. Finally, a numerical example for the proposed control scheme is presented.

The two reviews and five papers in this special issue focus on industrial applications of holonic manufacturing systems.

The major impetus for the use of RFID technology is tracking personnel and objects to monitor and control movement. Traditionally, this task is accomplished using a centralized systems architecture in which every event is transmitted to a host computer for validation. Distributed intelligent systems are based on two principles: distributed communications and distributed intelligence. Together, these functionalities enable the implementation of networks that are highly robust, scalable, flexible, and facilitate their integration with client/server systems. We describe how RFID can be implemented using distributed intelligent systems to automate data collection for service queues, track and control personnel and goods, monitor and control inventory, and use dynamic digital signage for information dissemination.

Due to the advents of multi-core CPU and GPU, various parallel processing techniques have been widely applied to many application fields including computer vision. This paper presents a parallel processing technique for realtime feature extraction in object recognition by autonomous mobile robots, which utilizes both CPU and GPU by combining OpenMP, SSE (Streaming SIMD Extension) and CUDA programming. Firstly, the algorithms and codes for feature extraction are optimized and implemented in parallel processing. After the parallel algorithms are assured to maintain the same level of performance, the process for extracting key points and obtaining dominant orientation with respect to the key points is parallelized. Following the extraction is the construction of a parallel descriptor via SSE instructions. Finally, the GPU version of SIFT is also implemented using CUDA. The experiments have shown that the CPU version of SIFT is almost five times faster than the original SIFT while maintaining robust performance. Further, the GPU-Parallel descriptor achieves acceleration up to five times higher than the CPU-Parallel descriptor at a cost of a bit lower performance.

Currently, only Xilinx field programmable gate arrays (FPGAs) support dynamic partial reconfiguration (DPR). While there is currently some computer aided design (CAD) tool support for ISE-based DPR designs, none exists for microprocessor-based designs created in EDK. Creating DPR systems with the limited tool support currently available for ISE-based systems is already a challenging and complex process for novice DPR designers. These difficulties are severely compounded for potential microprocessor-based designs requiring a significant learning curve for novice DPR designers before they can successfully create their first working DPR system. This paper presents preliminary work towards extending the automation in Xilinx®'s current DPR design flow to include microprocessor based systems. The objective is to abstract low level details for novice designers, allowing them to focus on learning how to improve the quality of their design as opposed to how to perform the necessary manual transformations to generate a preliminary functional design. A case study demonstrated that the learning curve required to implement a first working design could be reduced by more than a factor of 15 times by improving the current automation available for microprocessor-based EDK designs.

Currently Xilinxpsilas dynamic partial reconfiguration (DPR) model requires the size and number of partially reconfigurable (PR) regions to be fixed during the design phase. Only one PR module may be active per PR region at any given time. This paper presents a new DPR model that replaces the current multi-PR region model with a single partially reconfigurable domain (PR Domain). Multiple PR modules of different sizes are able to concurrently reside in the PR domain. PR modules may be loaded to any portion of the PR domain given that sufficient resources exist. Future PR modules can be designed with dimensions up to those of the PR domain. A case study with multiple PR modules of varied sizes is used to demonstrate the adaptability and flexibility of the PR domain model.

Attributes of an object contain its fundamental properties. Attribute data is the main source of clustering information. Although relationship data is an extrinsic property of objects and is at least as important as attribute data, most clustering methods process only one type of characteristic data. However, attribute and relationship data must be analyzed together for applications such as market segmentation, social network segmentation, and image segmentation. In this study we describe a new algorithm that combines attribute and relationship data for joint clustering analysis. An experimental evaluation demonstrates the usefulness and accuracy of the proposed algorithm when applied to image segmentation.

A distributed system appears to be a promising approach to resolving critical networking limitations prevalent in a centralized topology. Extensions are required to current distributed software platforms to facilitate a better distributed system. This paper examines the architecture of two distributed software platforms, JADE and JXTA and proposes architectural extensions for a better distributed system. The extensions are discussed and implemented. It is shown that JADE is a superior platform in terms of efficient and latency, mainly due to the partially centralized approach of its agent management system. JXTA has advantages due to its de-centralized management system and unrestricted scalability.

Decentralized software architectures are essential to fully realize the potential of distributed networks. However, developers are burdened with the need to create a communications infrastructure for a distributed system along with their applications. The use of a generic communication interface greatly simplifies the process, thereby allowing developers to focus on applications. This paper describes the design and functionality of such an interface.

Clustering is one of the basic data mining tasks that can be used to extract hidden information from data in the absence of target classes. One of the most well-known density based clustering algorithms for processing spatial data is Density-Based Spatial Clustering of Application with Noise (DBSCAN) that uses learning parameters epsiv andminPtsto define the density that will be sought in the data set while forming the clusters. The major drawbacks of the DBSCAN algorithm are its sensitivity to user input required to execute the algorithm, inability to recognize clusters with different densities, and computational complexity. In this study, we propose a three-level clustering method to address the second issue. The first level selects appropriate grids so that the density is homogeneous in each grid. The second stage merges cells with similar densities and identifies the most suitable values of epsiv andminPtsin each grid that remain after merging. The third step of the proposed method executes the DBSCAN method with these identified parameters in the dataset. The proposed method is tested in three artificial benchmark data sets to demonstrate that the clusters are correctly identified.

A rough mill is a manufacturing facility where loads of lumber (jags) are processed into specific size components. In this paper, we describe a multi-agent system that simulates the operations of the ripsaw, conveyor and chopsaw, and provides the user with recommended decisions for selecting jags and cut-lists (specific-size components for cutting). Using the graphical user interface, the user can run several scenarios, and test the recommended decisions through simulation. The operator can then make an informed decision on the rough mill floor. A discrete event based simulation model provides functionality for the agent-based model. The Java Agent Development Framework (JADE) was used to develop the agent system. The new system was validated by comparing results obtained using a centralized simulator.

Distributed energy systems involve localized sources contributing to a common power grid. An issue facing distributed energy systems is a suitable control scheme that enables to the greatest extent possible the potential scalability and robustness in distributed generation. One approach to controlling distributed energy systems is through multi-agent technology. By representing each power source and load as an autonomous intelligent agent, distributed coordination can be implemented where agents negotiate among themselves to satisfy power demand. An agent-based approach using contract-net coordination is demonstrated through software simulation, with the necessary communication and coordination structure to create a scalable and robust system.

Industrial robotics have looked to vision systems for flexibility. This promise has largely been unrealized because existing systems are either too slow or too inaccurate. Both visual servoing and traditional look and move are insufficient because visual servoing requires too much bandwidth, and look and move requires very accurate calibration. To mitigate these effects, we have designed a hybrid system. Our hybrid system is composed of a roughly calibrated look-and-move system using a linear approximation, and a gain scheduled PD controller which performs visual servoing. The system performs markedly better than visual servoing or look-and-move techniques in isolation. This system have many potential applications including bin-picking, sorting, and tele-operation.

Raw material cost is one of the major contributors to the overall cost in rough mill operations. The challenge is to choose raw materials that can fulfil a given order in a reasonable time. However, the objective of minimizing raw material cost conflicts with the objective of minimizing the processing time. This study investigates the use of a local search mechanism to find the best jag sequence for a given order. Simulation is used to evaluate the performance of each jag sequence candidate with respect to the objective function. Since the proposed method is intended for real-time production, beam search is utilized. Numerical results for a sample order list show 22% cost reduction.

Data warehouse systems typically designate downtime for view maintenance, ranging from tens of minutes to hours depending on the system size. We develop a multiagent system that achieves immediate incremental view maintenance (IIVM) for continuous updating of data warehouse views. We describe an IIVM system that processes updates as transactions are executed at the underlying data sources to eliminate view maintenance downtime for the data warehouse-a crucial requirement for internet applications. The use of a multiagent framework provides considerable process speed improvement when compared with other IIVM systems. Since agents are used to delegate the data sources and warehouse views, it is easy to reorganize the components of the system. Through the use of cooperative agents, the data consistency of IIVM can be easily maintained. The test results from this research show that the proposed system increases the availability of the data warehouse while preserving a stringent requirement on data consistency.

This research treats a design for reconfigurable robotic systems with large variations in configurations. To evaluate system adaptability, we define the configuration space to be the set of all feasible configuration variations of the robotic system. We define the volume of the configuration space expressed in terms of physical structures to be a measure of system reconfigurability and the volume of the configuration space expressed in terms of Denevit-Hartenberg notation to be a measure of system adaptability. We develop an evaluation method to determine the architecture of reconfigurable robotic systems with high adaptability. A case study is presented to demonstrate that a reconfigurable robotic system with high reconfigurability may not have high adaptability. Finally, we describe how to achieve task-oriented configuration design of reconfigurable robotic systems.

A fuzzy decision-making system for multi-criteria robot motion planning and control is described for a constant speed omni-directional mobile robot with active stereo cameras capable of panoramic viewing. The robot can be commanded to move to a target point through an unknown environment while satisfying multiple criteria. Advantages of the proposed method are confirmed by simulation. A multi-agent approach is also described for path planning with multiple robots.

We describe a fully distributed approach to scheduling within a sliding time frame or sliding window. All agents with processes inside the window schedule operations using time shifting and a combinatorial reordering algorithm. Operations outside the window need not be scheduled until either the sliding window has advanced to encompass them or until gaps have opened between tasks inside the sliding window to accommodate them.

A rough mill production system is an unpredictable dynamic system for which the effects on production of many factors are strongly interrelated. A distributed decision support system for dynamic jag (a load of lumber) selection in defect sensitive production is proposed. Case-Based Reasoning and heuristic rules determine recommended jags for cut-lists in the decision process. Using a statistical method, cases are grouped by categorizing problems and solutions. Heuristic rules measure the similarity between current and past cases. The framework for a decision support system has two layers in which jag types are selected at the top level and specific jags are chosen on the bottom level. Decisions from different sources influence both top level and bottom level. The dynamic character of the system is taken into account by collaboration between distributed decision points that can change indices by retrieving previous cases and storing new cases. The recommended jags are tested by simulation and used for feedback to the decision support system. Finally, the system is validated by comparison with actual production.

This paper presents a method for tracking a human head based on the integration of camera saccade and chromatic shape fitting, which are implemented as functional modules in an active tracking system. Head motion is detected in the saccade module by extracting edges from two successive images. The position of the head in the current image is approximated as the centroid of the apparition formed by the moving edges of the target. A visual position cue is used to drive a pan/tilt camera to perform real-time saccade keeping the target in the foveal area in the image. The shape-fitting module is invoked to extract more information from the target. The shape of the target is modeled as an ellipse whose position, orientation and size are dynamically determined by shape fitting, and implemented with a color registration technique. In the proposed method, quasi real-time pursuit is achieved using a Pentium II computer in an uncontrolled environment with arbitrary relative motion between the target and camera.

Image transfer is a method for projecting a 3D scene from two or more reference images. Typically, the correspondences of target points to be transferred and the reference points must be known over the reference images. We present two new transfer methods that eliminate the target point correspondence requirement. We show that five reference points matched across two reference images are sufficient to linearly resolve transfer under affine projection using two views instead of three views as needed by other techniques. Furthermore, given the correspondences of any four of the five reference points in any other view, we can transfer a target point to a third view from any one of the two original reference views. To improve the robustness of the affine projection method, we incorporate an orthographic camera model. A factorization method is applied to the reference points matched over two reference views. Experiments with real image sequences demonstrate the application of both methods for motion tracking.

This research presents a multi-fingered hand and computer control system intended for research in dextrous manipulation. The hand mechanism is based on an anthropomorphic configuration with four identical fingers. Each finger has four degrees of freedom actuated by four DC servomotors. The fingers, palm and mechanical interface to a robotic arm are separate components of a modular design allowing the hand to be highly dexterous and flexible. Each finger is a compact module with eight position sensors, and all the four actuators are integrated into the mechanical structure of the finger module. Position control has been implemented using a DSP based computer controller. Experimental results validate that the basic functionality and requirements of the hand system were achieved.

Research on robotic grinding has emphasized process parameter control. When an industrial robot is used to remove excess material from castings, grinding weld beads, or welded surfaces, excessive vibrations often occur. Methods based on force control can improve the response. In this paper, we present practical methods for vibration reduction, feed-speed/force control, and an optimal configuration of a 4-DOF redundant robotic manipulator for grinding welded surfaces. An optimal configuration of the robotic manipulator is derived to minimize the arm compliance. The proposed method maximizes the robotic arm stiffness to reduce vibrations. The arm, parameters, and PID control were simulated using ADAMS/view and ADAMS/controls under MATLAB. The grinding force was considered as an input to the dynamical system in addition to the torque/force inputs at each joint. DC servomotors were modeled for actuation of each joint and the PID controller was tuned by the Ziegler-Nichols second rule. Simulation results demonstrate that feed speed/force control reduces vibrations, and provides the capability to use the robotic manipulator for profiling.

Production scheduling in wood product plants, such as furniture factories, is highly complex due to its sensitivity to defects occurring in wood. Due to the huge number of choices and uncertainty of the outcome an optimum schedule cannot be computed mathematically. These choices, with complex interdependencies, have to be made on an hourly basis at different machines and must be coordinated to achieve the overall production,objectives. A decision support tool, using a 3D simulation model, is provided to predict the production performance of the null under various operational schedules, before a selected schedule is implemented. A 3D simulation model was developed accurately depicting the layout and operation of a rough mill. A historical database, some of it maintained via human input and some of it collected automatically, was analyzed to provide the basis for predicting the behavior of the mill when processing different type of raw materials and when producing different combination of products. The validated model, which links to the scheduling database (i.e., raw material available, products required) is used to test-fly alternate production schedules as often as required, thus identifying potential production problems before they occur in the mill. The next step will be to incorporate intelligent scheduling agents using techniques, such as fuzzy logic and genetic algorithms, to provide scheduling recommendations on individual machines. In the future these will be coordinated in a holonic manufacturing execution system to achieve better global performance. Performance measurement will require assessment based upon multiple criteria (e.g., productivity, recovery, grade utilization, and satisfaction of order files).

This paper treats the kinematic control of manipulators with redundant degrees of freedom. We derive an analytical solution for the inverse kinematics that provides a means for accommodating joint velocity constraints in real time. We define the motion optimizability measure and use it to develop an efficient method for the optimization of joint trajectories subject to multiple criteria. An implementation of the method for a 7-dof experimental redundant robot is present.

Grasping robotic hands is classified into three categories based on the object connectivity. We decompose the space of contact forces into four subspaces and develop a method to determine the dimensions of the subspaces with respect to the connectivity of the grasped object. The relationships we obtain reveal the kinematic and static characteristics of three categories of grasps. It indicates how contact forces can be decomposed corresponding to each type of grasp. The technique also provides a guideline for determining the distribution of contact forces on grasped objects. We analyze how power grasps are identified from the object connectivity and used to synthesize hand configurations for grasping and manipulation tasks. A physical interpretation of the subspaces and the determination of their dimensions are illustrated by examples.

Gait analyses show that knee moments are considerably different when walking on different terrain. To accommodate changing conditions, prostheses should provide a means for adjusting the knee moments by identifying conditions of the terrain. In this research, terrain identification is obtained by the use of electromyographic (EMG) signals that are used to control resistive moments of an above-knee prosthesis. Results from laboratory experiments demonstrate that the technique is effective for identification and adaptable to different terrain.

Shop floor control is typically implemented with a centralized supervisory control system. Holonic control, a form of distributed control, provides a more robust control environment and improves production performance. The authors create a 3D virtual manufacturing environment to compare hierarchical control with holonic control. We use this virtual environment to analyze alternative approaches and quantify their effects on the system behavior in a controlled environment. Finally, we present a measure of robustness derived from reliability theory and utilize it for comparisons.

Automated guided vehicle (AGV) systems traditionally utilize a central controller to assign transportation tasks among vehicles. Because of its rigidity, a centralized architecture may not suitable for modern manufacturing with its rapidly changing markets, demands for products with higher quality, smaller batch sizes, customer specifications, and shorter delivery times. This research applies concepts from holonic manufacturing systems to develop a distributed AGV control system that is flexible and robust in the presence of disturbances. We present the architecture of the holonic manufacturing system, a coordination strategy based on contract nets, and simulation results that indicate an improvement in utilization when compared with traditional centralized control.

Describes a vision-guided telerobotic system that enables people with disabilities to perform clerical or office tasks. By adding a light-duty robot to the office workspace, the operator can manipulate files and perform other work-related tasks. To increase the effectiveness of the robot, vision can be used to verify that the robot is correctly positioned. In addition, vision can be be coupled with the telerobotic system to allow the user more intuitive control over the robot. Visual servoing and traditional computed kinematics actions are inappropriate for this application because visual servoing requires an excessive number of iterations and computed kinematics requires accurate calibration. To counteract these difficulties and to provide user functionality, we have designed a hybrid computed-kinematics telerobotic system with an initial coarsely-calibrated computed-kinematics step followed by a more accurate visual-servoing step. We show that there are significant performance benefits from this approach. Finally, we describe how the hybrid system may be utilized in an office environment.

This research describes the implementation of a vision-based algorithm that is capable of rapidly determining robotic grasp points for planar objects. A representation of the target and a quadtree expansion generate candidate grasps that are compared using a cost function. The approach returns the first acceptable grasp point at a given tree resolution. The system has an execution time on the order of seconds and it is suitable for a large number of planar or near planar objects.

An essential problem of image based visual servoing is evaluating the inverse Jacobian which, relates changes in image features to the change in robot position. Neural networks can learn to approximate the inverse feature Jacobian. In addition, neural networks have been used in dimensionality reduction of image input. We show that it is possible to use neural networks for both feature extraction using compression and for feature Jacobian approximation in the visual servoing problem. In our system, we consider the following feature extraction methods: geometric features, averaging compression, vector quantization, and principal component extraction.

This research concerns a grasp-planning algorithm that is fast and capable of determining grasp points for planar nondegenerate objects. We use a novel representation of the target and a quadtree based sampling scheme to generate a set of candidate grasps which are evaluated using a cost function. This function returns the first acceptable grasp point it finds. The resulting system has an execution time of seconds and is suitable for a large number of planar grasp planning problems.

A new electrorheological fluid joint damper based on orifice restriction has been developed for semi-active vibration control. The damper is capable of providing a continuously variable damping torque in response to an electric field. A mathematical model of the damper is developed and the influence of model parameters on the damping torque is analyzed. Performance tests show that the magnitude of the output torque increases 1.6 times within 10 milliseconds.

To realize control of robotic manipulators with redundant degrees of freedom, the concept of a motion optimizability measure is introduced. We derive an optimal solution technique for the inverse kinematics of a redundant robot that achieves real-time control with multiple performance criteria. Using this technique, we propose an efficient method for kinematic control. Experimental results are presented for a 7 DOF manipulator.

There is a need for robots that are more flexible and reliable than the fixed configuration models currently available. Redundant robots provide an alternative to satisfy this requirement because redundancy can be used to improve the kinematic performance and compensate for joint failures. Due to the uncertainty of potential failures and large accumulated path errors, the instantaneous joint torques may increase and exceed actuator limits during the system recovery process. We propose to alleviate this difficulty by the use of optimal redundancy control, an approach that simultaneously takes into account both kinematics and dynamics. To realize dual-optimization control, a dynamically redundant mechanism with local degrees of freedom is introduced, and its use for redundancy control is investigated. Simulation results demonstrate the proposed method.

The paper treats a fuzzy-neural tuned genetic algorithm for solving a constraint satisfaction problem for an industrial application. It describes the design of a reflecting lamp composed of five consecutive straight mirror segments that satisfy both illumination efficiency and uniformity properties. An analytically established neural network dynamically controls the genetic algorithm mutation rate and the convergence criteria. The neural network implements a six-rule fuzzy system that gains its knowledge from a human operator and works in a similar way to monitor the convergence process. Using numerical experiments the lamp configurations are determined. The proposed method can also be applied to other optimization design tasks.

Three degree of freedom planar mechanisms occur in nature and are fundamental to many robotic devices. This paper concerns the use of evaluation criteria, developed by the authors, to select the link lengths of 3 DOF planar manipulators and analyze their operational performance. The technique has wide application to the design of serial and parallel robots.

This paper discusses the swing-up control of a two link robot mechanism known as the Acrobot. First a PD controller is investigated and then a fuzzy controller is implemented by a combination of genetic algorithms, dynamic switching fuzzy systems, and meta-rule techniques. Limitations of the PD controller and the fuzzy controller are shown by investigating the effect of external random disturbances on the Acrobot using simulation. Design considerations are discussed. This study illustrates how intelligent control methods can reduce development effort and system complexity while achieving better performance.

We investigate methods for evaluating grasp configurations of multifingered robot hands. When a grasped object is subjected to externally applied forces and moments, an equilibrium of the object is achieved by contact forces which are generated by the joint torques of the fingers. Assuming that the object and fingers comprise a rigid body system, we provide a general formulation relating the contact forces with the joint torques, external forces, and moments. We define three criteria to evaluate optimal grasp configurations. The computation of the criteria requires determining eigenvalues of a matrix. The method is applicable to all types of grasps. It is not limited by the number of contacts for each fingers, the geometry of the object, nor the contact models. In the examples, several grasp configurations are compared using these criteria.

This paper describes experimental results from a study of neurocontrol applied to a Yaskawa industrial robot. We investigate the use of a hybrid control structure that has superior features and improves the approximation and generalization capability of the neurocontroller. The control structure has guaranteed stability. The results show that the technique has rapid learning speed and excellent performance in a wide range of manipulator tasks. The experiments also demonstrate that the control structure is easy to implement in industrial environments.

This research characterizes grasping by multifingered robot hands through an investigation of the space of contact forces between fingers and the grasped object. By decomposing the space of contact forces into four subspaces, we develop a method to determine the dimensions of the subspaces with respect to the connectivity of the object. The relationship we obtain reveals the differences between three types of grasps classified in the paper and indicates how the contact force can be decomposed corresponding to each type of grasp. Therefore, it provides a guideline for formulating the distribution of contact forces as a basis for optimization. The subspaces and the determination of their dimensions are illustrated by examples.

The determination of contact forces between a grasped object and fingers of a robot hand is treated in this research. In previous research on fingertip grasps, the underlying assumption is generally that the fingers can apply any required force. In cases of enveloping or power grasps, the latter assumption does not always hold because same components of the contact forces may not be controllable. These uncontrollable forces need to be separated in the representation of contact forces to ensure that the contact forces are obtained by adjusting the controllable components of the contact forces. This paper provides a method to solve this problem. We decompose the space of contact forces into four subspaces. Based on this decomposition, the contact forces can be explicitly represented with respect to the joint torques. Therefore, the application of the technique leads to a controllable solution. Three examples are provided to illustrate the decomposition.

We describe an approach for planning grasps of multifingered robot hands based on a small vibration model. Using features of the grasp configuration, we analyze asymptotic stability, contact situations, and uniaxial fingertip force constraints for the combined planning of finger posture and finger position, and characterize the generalized mass, damping, and stiffness. Choosing the largest time constant of the vibration model as an optimization criterion for planning finger postures and positions, the original problem of dynamic grasp planning is formulated as a nonlinear program. Simulation examples for a three-fingered robot hand grasping a spherical object demonstrate the effectiveness of the approach.

A new electrorheological fluid damper has been developed to control the elastic vibrations of robotic mechanisms. The damper is capable of providing a continuously variable damping torque in response to an electric field. In the absence of an electric field the device acts like a normal fluid damper that produces a viscous damping torque. When the field is energized the device develops a Coulomb damping torque that is much greater then that produced by conventional viscous damping. The influence of model parameters on the damping torques is analyzed in this paper. Simulation results show that this damper can cause joint vibrations to quickly decay.

This research treats grasping of an object by a multifingered robot hand. By decomposing the space of contact forces exerted between the fingers and the grasped object into subspaces we develop a method to determine the dimensions of the subspaces with respect to the connectivity of the grasped object. This approach provides insight into different grasps based on a classification into three types. A power grasp is defined when the connectivity of the grasped object is equal to or less than zero. The analysis of contact force distribution is simplified for a power grasp with zero connectivity. Examples for dimensional determination are illustrated.

To realize the control of redundant manipulators, the concept of the motion optimizability measure is introduced. We derive an analytical solution technique for the inverse kinematics of a redundant robot that reduces the computational complexity and does not require the pseudoinverse Jacobian. Based on this technique, we propose an efficient, kinematic optimal control scheme. We show how to incorporate multiple criteria in the formulation. An online implementation of the system that ensures stable operation is presented.>

This research concerns the relationship between distance accuracy and positioning accuracy for robotic manipulators. We propose an approach for calibration and verification of the positioning accuracy based on a polynomial approximation to the workspace. Utilizing singular value decomposition a method is developed for distance error compensation. Computed results show that the distance accuracy and positioning accuracy of the robot can be improved by use of the proposed technique. The technique is illustrated for a PUMA 560 industrial robot.>

The grasping stiffness and the contacting stiffness for the grasping system of a multifingered robot hand are characterized. Using a Lagrangian formulation, the authors develop the small displacement vibration equation of the grasping system. Based on the features of a grasping state, they characterize object stability, contact stability, contact position, and uniaxial fingertip force constraints for grasp planning. From the asymptotical stability of the vibration system, a quality measure is defined that is used as an objective for grasp planning, and grasp planning is formulated as a nonlinear programming problem. An example for a three-fingered robot hand grasping a spherical object demonstrates the applicability and effectiveness of this approach. Numerical results using a constrained conjugate direction descent technique are described.>

Robotic systems have advantages for recovery and identifiation of objects in hazardom environments. Under such conditions it may be impractical to use visual, acoustic or electromagnetic sensors for detection. At the Center for Robotics and Manufacturing Systems of the University of Kentucky, a three-fingered dextrous hand is being integrated with 3-0 tactile data acquisition and pattern recognition to develop the Tactile Object acquisition and Correlation Hand (TOUCH) system. We describe the 3-0 data acquisition algorithms for determining finger-tip positioning patterns and sampling 3-0 coordinutes of the object by sensing forces at the finger-tips. The result of this sampling is a 3-0 polyhedron enclosing the touched object. A second function of thepositioningpatterns is to acquire mass features while grasping and moving the object.

A fast and simple algorithm for determining optimal grasps of a planar multifingered robotic hand is presented. Using a representation for the stiffness of a planar grasp system, the authors derive conditions for static equilibrium, task-oriented grasping, and stability. An optimization model for determining optimal grasps of a planar multifingered hand is established using a quality measure which includes the effect of the external disturbing forces and moments. A constrained gradient descent technique is used to compute the optimal grasps. An example demonstrates the applicability and effectiveness of the theory.>

The development and implementation of an advanced control system for a seven-link, 12-degree-of-freedom, biped robot in the double-support phase are addressed. A constrained dynamic model of the biped robot is formulated and a reduced order model for the double-support phase is derived. In this model the dependent variables are related to the independent variables through the kinematic Jacobian. Control strategies based on feedforward compensation and linear state feedback are derived for tracking specified joint trajectories. The approach is demonstrated using results of a sway motion obtained from a prototype biped robot that has been constructed.>

A neural network architecture for the control of a three-link biped walking robot is developed. The neuromorphic controller, based on hierarchical structure of artificial neural networks, is trained by supervised learning. The training model is derived by applying nonlinear feedback decoupling and an optimal tracking strategy. The neurocontroller utilizes several computational features of neural networks-generalization, parameter adaptivity, and robustness. Based on a comparison of the system performance using an optimal control law, it is concluded that the neurocontroller provides superior performance in the presence of large disturbances.>

A fingertip force decomposition model for a multifingered robot hand grasping and manipulating an object is proposed. During the trajectory execution the fingertip force is decomposed into a dynamic equilibrating force and an internal interaction force. Using the equations of motion and the displacement consistency relationship of the virtual grasping system, a computational algorithm is derived for the dynamic equilibrating forces subject to the constraint of dynamic stability. To simplify the formulation, a representation of the internal interaction force components is developed. An objective function based on the fingertip forces is defined and the internal interaction forces are optimally determined. A computational algorithm for planning fingertip forces during trajectory execution is derived.>

A method for planning collision-free trajectories of two SCARA robots in a common workspace is described. The robots are treated as a single redundant system. A collision map representing the intersection of the robots is developed in a two-parameter space. A trajectory is planned by finding a collision-free path in the parameter space as a primary constraint and minimizing an objective function in joint space as a secondary goal. An artificial potential field facilitates path planning in the parameter space. A gradient projection method minimizes the error between the current and desired joint angles and optimizes other criteria. The proposed formulation has application in flexible assembly cells which utilize multiple SCARA robots. Two examples demonstrate the effectiveness of the method.>

The synthesis and verification of biped walking trajectories during the single-support phase is discussed. The biped is modeled as a seven-link twelve degree-of-freedom anthropomorphic robot. By utilizing the zero moment point (ZMP) and the equivalent force-moment, the physical admissibility of the biped walking is characterized. For physically realizable walking during the single-support phase, the trajectory of the ZMP on the ground must be inside the stable region of the supporting sole. A biped walking trajectory specified by eight pattern parameters is derived through inverse kinematics. ZMP trajectories for different walking patterns and the influence of the pattern parameters on the ZMP trajectories are presented.>

A method is presented for path planning of a point robot moving among polyhedral obstacles with piecewise constant translating velocity. Representing the obstacles as polyhedra in the space-time domain allows a collision-free, minimum-time path to be obtained using graph search and linear programming. The planner views the space-time configuration of free space as disjoint polytopes where each point in the space-time domain is mapped into a unique polytope. The planner searches connected polytopes between the start and goal polytopes that satisfy the speed and time constraints. A near-optimal trajectory is determined by constrained optimization. In the proposed approach, the obstacle is allowed to move faster than the point robot, and the methodology can be easily extended to motion planning in higher-dimensional spaces.>

A unified approach suitable for path planning with moving polyhedral obstacles is presented. The planner views the space-time configuration of free space as disjoint polytopes that represent a time-dependent environment consisting of moving and stationary objects. Each point in the space-time domain is mapped into a unique polytope set. The planner then constructs a family of feasible collision-free trajectories by searching connected polytopes between the start polytope and the goal polytope that satisfy the speed and time constraints. Finally, a near-optimal trajectory is determined by constrained optimization. This approach does not require that obstacles be nonoverlapping or noncolliding. In addition, the obstacle is allowed to move faster than the planned robot. However, the speed of the obstacle must be piecewise-constant. The proposed approach can be easily extended to motion planning in higher dimensional spaces.>

Machine vision offers manufacturing industries a more cost-effective means of developing and implementing robotic applications. How using a vision sensor can increase the flexibility and usefulness of robots in specific manufacturing applicatons is described, provided that specific features of the robot-vision application development environment are present. These features include an object model representation that incorporates both statistical and relational information, a robot-vision interface that accommodates the flow of data and control between the vision sensor and the robot controller, and an integrated user progranunng environment that allows the development of object-oriented robotic applications. A system is described that incorporates these features and some requirements for future development of robot vision are given.

A working example of a merger of three system science techniques, simulation, evaluation, and optimization is presented. A system dynamics model of energy production in the United States is used to calculate the effects of various energy policies, while a multiattribute measurement model is used to evaluate those effects. Optimization procedures are used to find the policies that lead to the `best' performance of the simulation model when judged in multiattribute fashion. Results are presented for both a simulation model that uses over 300 variables and 5 policies and a multiattribute evaluation model with a dozen attributes.

Eight commercially available high-level robot programming languages developed by industrial robot builders and research laboratories are evaluated. These languages are: AL; AML; Help; Jars; MCL; Rail; RPL; and Val. The historical background of the languages is reviewed. The languages are evaluated on the basis of data types, control structures, motion specification, use of sensors, and interface with external machines and devices. Common and uncommon features are noted. Facilities for program editing, entry, debugging, and teaching are compared. Conclusions are given regarding their present status and future development.

The formulation and algorithmic solution of a class of optimal control models is discussed for integrated production, inventory, and research and development (R&D) planning. The model is based on the constrained minimization of the cost of labor, capital, and R&D engineering subject to a production constraint utilizing a Cobb-Douglas type input-output function. The solution technique utilizes a modification of a gradient projection algorithm due to Demyanov and Rubinov. Numerical results include a sensitivity analysis of the cost structures.