In computer-aided architectural design, words are an underemployed source of information. Through a series of case studies, we deduced a design annotation data model. All entities in this model can be captured from the design draft, except one: the word relation. Therefore, a system was developed that generates word graphs using single words from the draft as input. The system searches for semantic relations between words and for new intermediate words that can connect two existing words. The system has filters that select only those graphs that are considered interesting by the designers. The envisioned applications of word graphs in the context of computer-aided architectural design are to contribute to the architect's design and to enhance the fluency of the design. These expectations are met, but must be considered in relation to the architect's drafting behavior.

The system here described has the capability of generating range images that include robot motion. The system has two main modules, the motion and the image generator. Motion is modeled using a Bezier's curve method. To compute a range value corresponding to a pixel image, the robot position in the coordinated system is obtained from trajec-tory generation. In this way, distortion is produced in the image, or sequence of images, as a consequence of motion. The obtained range images represent scenes perceived by the robot from a specific location or during a specified dis-placement in a very “real” view.

Tools that make it possible to measure the performances of manipulators are essential in many technical applications, for instance, when the optimal path to accomplish a task has to be chosen, or when different manipulator architectures have to be compared. This paper proposes some indices that fully describe the passive dynamic performances of manipulators with two degrees of freedom (dof). The pro- posed indices make it possible to compare the passive dynamic performances of different manipulator architectures, which can perform the same tasks, and can be used to build diagrams which highlight the effects of variations in the manipulator geometry on the manipulator dynamics. These features make them easy to be used in a design context. Finally, some applications of the proposed indices will be presented and discussed.

This paper focuses on the structure and property of the singularity loci of the 3/6-Stewart-Gough platform for general orientations. Based on the singularity kinematics principle, a planar singularity-equivalent-mechanism is proposed, by which the complicated singularity analysis of that parallel mechanism is transformed into a simpler position analysis of the planar mechanism. All the possible positions of the planar mechanism form the singularity loci of the 3/6-Stewart-Gough manipulator. The result shows that the singularity equation become quite simple moreover the structure and property of the singularity loci are also identified and explained. For the most general orientations of the typical 3/6-Stewart-Gough platform, the singularity locus equation is a special irresolvable polynomial expression of degree three, which in infinite parallel principal sections includes a parabola, four pairs of intersecting straight lines and infinity of hyperbolas. This result is beneficial to analysis of the similar issue of other Stewart-Gough manipulators.

A novel composite control scheme for a manipulator with flexible links and joints is presented that uses the singular perturbation technique (SPT) to divide the manipulator dynamics into reduced order slow and fast subsystems. A neural network controller is then applied for the slow subsystem and a state-feedback H∞ controller for the fast subsystem. Results are presented that demonstrate improved performance over an alternative SPT-based controller that uses inverse dynamics and LQR controllers.

In this paper, we have developed and implemented a system that combines autonomous obstacle avoidance with force-reflective tele-operation. In this system, a tele-operated mobile robot is controlled by a local two-degrees-of-freedom force-reflective joystick that a human operator holds while he is monitoring the screen. The force-reflective joystick transforms the relation between a mobile robot and the environment to the operator as a virtual force. A virtual force is generated in the form of a new collision vector and reflected to the operator, which makes the tele-operation of a mobile robot safe from collision in an uncertain and obstacle-cluttered remote environment. A mobile robot controlled by a local operator usually takes pictures of remote environments and sends the images back to the operator over the Internet. Because of limitations of communication bandwidth and the narrow view-angles of the camera, the operator cannot observe shadow regions and curved spaces. To overcome this problem, a new form of virtual force is generated along the collision vector according to both distance and approaching velocity between an obstacle and the mobile robot, which is obtained from ultrasonic sensors. This virtual force is transferred back to a master (two degrees of freedom joystick) over the Internet to enable a human operator to feel the geometrical relation between the mobile robot and the obstacle. It is demonstrated by experiments that this haptic reflection improves the performance of a tele-operated mobile robot significantly.

A mathematic model is established to describe a swarm with multi-behavior. Regarding a swarm designed for cooperative task, we propose a model which includes a macroscopic model and a individual-based model. The macroscopic framework model describes global dynamics of swarms, which is normally expressed by dynamical populations' densities with different behaviors, while the individual-based framework model describes a individual agent's trajectory. Based on these models, we prove that all objects can be collected to the “home” area under conditions of individual agents subject to sensor constraints.

We present the positional abilities of a humanoid manipulator based on an improved kinematical model of the human arm. This was synthesized from electro-optical measurements of healthy female and male subjects. The model possesses three joints: inner shoulder joint, outer shoulder joint and elbow joint. The first functions as the human sternoclavicular joint, the second functions as the human glenohumeral joint, and the last replicates the human humeroulnar rotation. There are three links included, the forearm and the upper arm link which are of a constant length, and the shoulder link which is expandable. Mathematical interrelations between the joint coordinates are also taken into consideration. We determined the reachability of a humanoid arm, treated its orienting redundancy in the shoulder complex and the positional redundancy in the shoulder-elbow complexes, and discussed optimum configurations in executing different tasks. The results are important for the design and control of humanoid robots, in medicine and sports.

We advocate a declarative approach to proving properties of logic programs. Total correctness can be separated into correctness, completeness and clean termination; the latter includes non-floundering. Only clean termination depends on the operational semantics, in particular on the selection rule. We show how to deal with correctness and completeness in a declarative way, treating programs only from the logical point of view. Specifications used in this approach are interpretations (or theories). We point out that specifications for correctness may differ from those for completeness, as usually there are answers which are neither considered erroneous nor required to be computed. We present proof methods for correctness and completeness for definite programs and generalize them to normal programs. For normal programs we use the 3-valued completion semantics; this is a standard semantics corresponding to negation as finite failure. The proof methods employ solely the classical 2-valued logic. We use a 2-valued characterization of the 3-valued completion semantics, which may be of separate interest. The method of proving correctness of definite programs is not new and can be traced back to the work of clark in 1979. However a more complicated approach using operational semantics was proposed by some authors. We show that it is not stronger than the declarative one, as far as properties of program answers are concerned. For a corresponding operational approach to normal programs, we show that it is (strictly) weaker than our method. We also employ the ideas of this work to generalize a known method of proving termination of normal programs.

In this article, we present a learning model that can control the kinematics motion of a simulated anthropomorphic arm in reaching and grasping tasks of a static prototypic object placed behind an obstacle of varying position and size. The network, composed of two generic neural network modules, learns to combine multi-modal arm-related information (trajectory parameters) as well as obstacle-related information (obstacle size and location). We based our simulation on the Via Point notion, which postulates that the reach motion planning is divided into successive positions of the arm. In order to determine these particular positions, some specific parameters have been extracted from an experimental protocol and constitute the pertinent parameters to be integrated into the model. This net of neural net determines the total path able to reach and grasp the prototypic object while avoiding an obstacle.

We developed a new type of a human-sized BWR (biped walking robot) driven by the closed-chain type of a joint actuator. Each leg of the BWR is composed of three pitch joints and one roll joint. In all, a 12 degree-of-freedom robot, including four arm joints, was developed. The BWR was designed to walk autonomously; it is actuated by small 90W DC motors/drivers and is has DC batteries and controllers. A new type of the joint actuator for the BWR is composed of the four-bar-link mechanism driven by a ball screw which has high strength and high gear ratio despite its light weight.

In this paper, analyses on the four-bar-link mechanism applied to the joint actuator and on the structure of the BWR are presented. Through walking experiments of the BWR, the superior trajectory-tracking ability of the proposed joint actuator is validated.

The properties of the software part of a control system implemented in walking robots are described. The paper presents also the navigation method elaborated for a family of hexapods. The general structure of the programming system is given together with the functional description of the system modules. The event-based action scheme of the central part of the system responsible for data distribution and high level navigation is addressed in detail.

This paper presents a technique for the optimization of bound queries over disjunctive deductive databases with constraints. The proposed approach is an extension of the well-known Magic-Set technique and is well-suited for being integrated in current bottom-up (stable) model inference engines. More specifically, it is based on the exploitation of binding propagation techniques which reduce the size of the data relevant to answer the query and, consequently, reduces both the complexity of computing a single model and the number of models to be considered. The motivation of this work stems from the observation that traditional binding propagation optimization techniques for bottom-up model generator systems, simulating the goal driven evaluation of top-down engines, are only suitable for positive (disjunctive) queries, while hard problems are expressed using unstratified negation. The main contribution of the paper consists in the extension of a previous technique, defined for positive disjunctive queries, to queries containing both disjunctive heads and constraints (a simple and expressive form of unstratified negation). As the usual way of expressing declaratively hard problems is based on the guess-and-check technique, where the guess part is expressed by means of disjunctive rules and the check part is expressed by means of constraints, the technique proposed here is highly relevant for the optimization of queries expressing hard problems. The value of the technique has been proved by several experiments.

This paper presents a robust input shaping technique that significantly reduces (almost eliminates) the residual vibration of manipulation systems typified by a flexible-jointed robot manipulator. The technique consists of two stages. In the first stage, a ramp function is superimposed onto the main trajectory to be preshaped. In the second stage, the outcome of the first stage is convolved with a sequence of two impulses. The robustness of the technique to the uncertainties in the system natural frequency and damping ratio are quantified through simulation and experimental evaluation. Simulation and experimental results demonstrate that the technique is not only effective in reducing the residual vibrations, but also it is robust to the uncertainties of as ∓35% from the ideal value of the system natural frequency. Further, it has been found that the proposed input shaping technique is insensitive to the uncertainties in the damping ratio. The results allow us to suggest that the proposed technique is versatile and robust enough to apply it to the motion design of any flexible-jointed manipulation system making a point-to-point motion.

The overall design of Ca.U.M.Ha. (Cassino-Underactuated-Multifinger-Hand) for harvesting horticulture products is presented. Ca.U.M.Ha. shows an anthropomorphic design incorporating four underactuated finger mechanisms and a simplified contrasting thumb, which are all joined to a rigid palm. The pneumatic cylinders of the articulated fingers are operated in parallel in order to give an additional auto-adaptability on the object to grasp. An application of Ca.U.M.Ha. for grasping different shapes of apples is presented.

A computational algorithm is developed to find a dynamic motion trajectory of a mobile manipulator with flexible links and joints that will allow the robot to carry a maximum load between two specified end positions. A compact form of the linearized state space dynamic equations is organized as well as constraint equations. Then, the problem of finding a maximum load carrying capacity on flexible mobile manipulators is formulated as a trajectory optimization problem.

Due to the demands from the robotic industry, robot structures have evolved from serial to parallel. The control of parallel robots for high performance and high speed tasks has always been a challenge to control engineers. Following traditional control engineering approaches, it is possible to design advanced algorithms for parallel robot control. These approaches, however, may encounter problems such as heavy computational load and modeling errors, to name it a few. To avoid heavy computation, simplified dynamic models can be obtained by applying approximation techniques, nevertheless, performance accuracy will suffer due to modeling errors. This paper suggests applying an integrated design and control approach, i.e., the Design For Control (DFC) approach, to handle this problem. The underlying idea of the DFC approach can be illustrated as follows: Intuitively, a simple control algorithm can control a structure with a simple dynamic model quite well. Therefore, no matter how sophisticate a desired motion task is, if the mechanical structure is designed such that it results in a simple dynamic model, then, to design a controller for this system will not be a difficult issue. As such, complicated control design can be avoided, on-line computation load can be reduced and better control performance can be achieved. Through out the discussion in the paper, a 2 DOF parallel robot is redesigned based on the DFC concept in order to obtain a simpler dynamic model based on a mass-balancing method. Then a simple PD controller can drive the robot to achieve accurate point-to-point tracking tasks. Theoretical analysis has proven that the simple PD control can guarantee a stable system. Experimental results have successfully demonstrated the effectiveness of this integrated design and control approach.

In the paper we address a problem of controlling an oscilmotion with a robot. As the object we have selected a yo-yo. First we have measured and analysed the motion of different yo-yos. We have developed a simplified model of a yo-yo which has one degree-of-freedom, and the behaviour at the end of the string is modelled as an impact. Next, we discuss the control strategy. Our results show, that for playing a yo-yo it is important to start the upward motion before the yo-yo reaches the bottom position and the acceleration has to be reversed after the bottom impact. We present two control strategies: one based on predefined hand motion pattern and and the other generating the hand motion on-line. Both allow playing the yo-yo at a selected top height. The theoretical results have been proven by experiments on a real robot system.

This paper deals with the design and the experiments of the upper part of the ROBIAN biped robot. The motivation of the ROBIAN project is related to the study of the human being locomotion system. The major application of ROBIAN prototype is the development of a real testing bed of active/passive prosthesis devices enhancing research on the human being locomotion mechanism handicaps. The analysis of the wrench six components exerted by the upper part of a virtual manikin on the locomotion apparatus leads to the identification of two coupling relations. Based on the dynamic equivalence concept between mechanisms, the ROBIAN torso mechanism is identified. This concept leads to a four degrees of freedom mechanism able to reproduce the dynamic effects of the upper limbs during the walking gait. The mechanism parameters are optimized with respect to several design criteria and constraints. Then the prototype is built and mounted on the ROBIAN locomotion apparatus through a six components force sensor. Experimental results presented in this paper validate the proposed approach. The experimental coupling coefficients are identified. The influence of the masses motion on the ZMP trajectory are also given, showing the effectiveness of the torso mechanism contribution during a walking gait.

This paper discusses the modeling and control of a robotic manipulator with a new deburring tool, which integrates two pneumatic actuators to take advantage of a double cutting action. A coordination control method is developed by decomposing the robotic deburring system into two subsystems; the arm and the deburring tool. A decentralized control approach is pursued, in which suitable controllers were designed for the two subsystems in the coordination scheme. In simulation, three different tool configurations are considered: rigid, single pneumatic and integrated pneumatic tools. A comparative study is performed to investigate the deburring performance of the deburring arm with the different tools. Simulation results show that the developed robotic deburring system significantly improves the accuracy of the deburring operation.