Dynamic optimum design of a three translational degrees of freedom parallel robot while considering anisotropic property

By taking the Delta robot as the object of study, this paper presents the methodology of the dynamic optimum design of a three translational degrees of freedom parallel robot while considering anisotropic property. Taking the acceleration, velocity, and gravity components into account, the torque and power indices are adopted as the objective functions for the dynamic optimum design. The physical meanings of the objective functions are the maximum input torque and power of the actuating joints when the moving platform translates with assigned acceleration and velocity. The transmission angles, the determinant of the direct kinematic Jacobian matrix, the ratio of the machine volume to that of the desired workspace, and the difference between the radius of the base platform and the radius of the moving platform are adopted as the constraints for the dynamic optimum design in order to make the Delta robot have a good transmission behavior between the links, keep far away from the direct kinematic singular configuration, not to be a very tall and slender configuration, achieve the desired performance without large dimension and big building cost. The examples of the dynamic optimum design of the Delta robot based on the torque and power indices are presented in the simulation while considering the requirements of the maximum acceleration and velocity of the moving platform along the respective direction parallel to the x axis, y axis and z axis are varied. The conclusions are provided at the end of the paper.     

Marble mosaic tiling automation with a four degrees of freedom Cartesian robot

The art of mosaic has arisen thousands of years ago. Despite all those years and all the attention it has received till today, mosaic tiling is still being carried out manually and mosaic tiling processes have never been changed except the tool and material developments.     

Dimensional synthesis of a three translational degrees of freedom parallel robot while considering kinematic anisotropic property

By taking the Delta robot as the object of study, this paper deals with the methodology of the dimensional synthesis of the three translational degrees of freedom parallel robot while considering the kinematic anisotropic property. The velocity transmission index is employed as the objective function of the optimization design. The physical meaning of the velocity transmission index is the maximum of the input angular velocity when the moving platform translates with an assigned velocity. The determinant of the direct kinematic Jacobian matrix, the ratio of the machine volume to that of the desired workspace and the difference between the radius of the base and the radius of the moving platform are adopted as the constraints for the dimensional synthesis in order to make the Delta robot have a good transmission behavior between the distal links, keep far away from the direct kinematic singular configuration, not to be a very tall and slender configuration, achieve the desired performance without large dimension and big building cost. The example of the dimensional synthesis of the Delta robot is presented in the simulation while considering the maximum velocity requirements for the moving platform along the respective direction parallel to the x axis, y axis and z axis are varied. The conclusions are provided at the end of the paper.     

Towards human motion capture from a camera mounted on a mobile robot

This article describes a multiple feature data fusion applied to a particle filter for marker-less human motion capture (HMC) by using a single camera devoted to an assistant mobile robot. Particle filters have proved to be well suited to this robotic context. Like numerous approaches, the principle relies on the projection of the model's silhouette of the tracked human limbs and appearance features located on the model surface, to validate the particles (associated configurations) which correspond to the best model-to-image fits. Our particle filter based HMC system is improved and extended in two ways. First, our estimation process is based on the so-called AUXILIARY scheme which has been surprisingly seldom exploited for tracking purpose. This scheme is shown to outperform conventional particle filters as it limits drastically the well-known burst in term of particles when considering high dimensional state-space. The second line of investigation concerns data fusion. Data fusion is considered both in the importance and measurement functions with some degree of adaptability depending on the current human posture and the environmental context encountered by the robot. Implementation and experiments on indoor sequences acquired by an assistant mobile robot highlight the relevance and versatility of our HMC system. Extensions are finally discussed.     

Generation of jumping motion pattern for a hopping robot using genetic algorithm

This paper describes an application of genetic algorithm to generate a jumping motion pattern for a hopping robot. A central pattern generator is used to generate the motion pattern. The tuning parameters of the central pattern generator are regarded as genes and adjusted by the genetic algorithm, so that the hopping robot can jump continuously to the reference height with the minimum force. To realize online tuning of the parameters, new genetic operations such as few individuals, quick estimation, instant selection, and intentional mutation are introduced. The experimental results demonstrate the effectiveness of the proposed scheme. This work was presented, in part, at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

Motion coordination for industrial robotic systems with redundant degrees of freedom

This work investigates how to distribute in an optimum fashion the desired movement of the end-effector of an industrial robot with respect to the workpiece, when there are redundant degrees of freedom, such as a positioning table. The desired motion is given as a series of acceleration functions in respective time intervals. The constraints of the optimisation are the available acceleration limit of axes, such as the table axes, the upper bounds to velocity and displacement of each axis and the avoidance of singular point areas of the robot, as defined by its manufacturer. The optimisation criterion is minimum total work for the motion. A genetic algorithm was used to solve the problem. The fitness function of the genetic algorithm calls a kinematics and dynamics simulation model of the robotic installation constructed in Matlab™, in order to compute the work consumed and to check possible violation of constraints. Examples of straight line and circular movement are given to prove the concept. Results are encouraging, yet demand on computing power is high.     

Robust robot manipulator control with autonomous consideration algorithm of torque saturation

As each joint actuator of a robot manipulator has a limit value of torque, the motion control system should consider the torque saturation. Conventional motion control based on robust acceleration controller cannot consider the torque saturation and it often causes an oscillated or wrong response. This paper proposes a new autonomous consideration method of joint torque saturation for robust manipulator motion control. The proposed method consists of three on-line autonomous algorithms. These algorithms are the torque limitation algorithm in joint space, the adjustment algorithm of motion control in Cartesian space, and the adjustment algorithm of motion reference in Cartesian space. The robot motion control using the proposed algorithms realizes smooth and robust robot motion response.     

Tracking control of a closed-chain five-bar robot with two degrees of freedom by integration of an approximation-based approach and mechanical design

The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of the robotic system can be all adjusted by properly setting the parameters in the error transformation function. The radial basis function neural network (RBFNN) is used to compensate the complicated nonlinear terms in the closed-loop dynamics of the robotic system. The approximation error of the RBFNN is only required to be bounded, which simplifies the initial "trail-and-error" configuration of the neural network. Illustrative examples are given to verify the theoretical analysis and illustrate the effectiveness of the proposed algorithm. Finally, it is also shown that the proposed approximation-based controller can be simplified by a smart mechanical design of the closed-chain robot, which demonstrates the promise of the integrated design and control philosophy.     

A walking pattern generation method of humanoid robot MAHRU-R

This paper proposes an omni-directional walking pattern generation method for a humanoid robot MAHRU-R. To walk stably without falling down, a humanoid robot needs the walking pattern. Our previous walking pattern method generated the walking pattern with linear polynomials of the zero moment point (ZMP). It implemented the simple walking like forward/backward walking, side step walking and turning. However, this method was not sufficient to satisfy the various walking which is combined by forward/backward walking, side step walking and turning. We needed to upgrade the walking pattern generation method to implement an omni-directional walking. We use the linear inverted pendulum model consisted of ZMP and center of mass in order to simplify the computation of walking pattern. The proposed method assumes that the state of the following stride is same to the state of the current stride. Using this assumption of walking pattern, the proposed method generates the stable walking pattern for various walking. And the proposed scheme generates the ZMP trajectory with the quartic polynomials in order to reduce the fluctuation of ZMP trajectory by various walking. To implement the efficient walking pattern, this method proposes three walking modules: periodic step module, transient step module and steady step module. Each step module utilizes weighted least square method with future ZMP position information. The effectiveness of the proposed method is verified by simulations of various walking. And the proposed method is confirmed by the experiment of real humanoid robot MAHRU-R.     

A robust control scheme for asymptotic tracking of robot motion

In this paper, a controller structure is developed to provide for asymptotic tracking of robot motion. The design tool is the theory of hyperstability and the analysis has led to a simple and an easy-to-implement robust version of the inverse dynamics. Simulation studies are worked out to demonstrate the controller performance. A comparison with other methods is done to show the merits of the developed scheme vs. other recently developed schemes. The implementation and computational requirements of the control schemes are determined and shown to be within the capabilities of new control hardware.This work was supported by the Kuwait University Research Administration under Grant No. EE063.     

Mathematical model of an industrial robot with articulated configuration and six degrees of freedom

This paper analyses the load influence on a d.c. drive motor servo system for all six degrees of freedom of industrial robots with an articulated configuration. Through the analyses, the analytical equations of total inertia and gravitation moments of an industrial robot servo system for external coordinate function were obtained. A mathematical model of an electro-mechanical industrial robot system was also developed.     

A gait study for a one-leg-disabled hexapod robot

—As a remarkably strong point of a hexapod walking robot, it is considered that even if one of the six legs is disabled, static walking may be maintained by the remaining five legs. However, to maintain the static stability at maximum, a gait study for five-legged walking is a necessary factor. Hence, this paper describes a method of gait study for such a situation. Since it is very difficult to find a suitable gait by use of an analytical method without any model, such as a model based on insects' walking, we employed a programming method with the help of recent powerful computers. Some devices are applied to reduce the number of computations. As a result, we have obtained two kinds of gaits which can maintain the gait stability margin at a high level for a duty factor in the range of 0.6β < 1.     

Adaptive control of a looper-like robot based on the CPG-actor-critic method

Adaptability to the environment is crucial for mobile robots, because the circumstances, including the body of the robot, may change. A robot with a large number of degrees of freedom possesses the potential to adapt to such circumstances, but it is difficult to design a good controller for such a robot. We previously proposed a reinforcement learning (RL) method called the CPG actor-critic method, and applied it to the automatic acquisition of vermicular locomotion of a looper-like robot through computer simulations. In this study, we developed a looper-like robot and applied our RL method to the control of this robot. Experimental results demonstrate fast acquisition of a vermicular forward motion, supporting the real applicability of our method. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

A user study of command strategies for mobile robot teleoperation

This article presents a user study of mobile robot teleoperation. Performance of speed, position and combined command strategies in combination with text, visual and haptic feedback information were evaluated by experiments. Two experimental tasks were designed as follows: positioning of mobile robot and navigation in complex environment. Time for task completion and motion accuracy were measured and compared for different command strategies and types of feedback. Role of haptic, text and visual feedback information in combination with described command strategies is outlined.     

Parametrization of stabilizing controllers for multivariable servo systems with two degrees of freedom

A necessary and sufficient condition for the existence of a servo controller is derived using the fractional representation approach for the plant, whose measured variables are not necessarily coincident with its controlled outputs. An independent parametrization of the servo controllers and the attainable transfer characteristics is proposed. The possible classes of all controllers with integrity in the error channel or measured output channel is also clarified using the derived parametrization.     

Analytic generation of workspace using the robot kinematics

When designing workplaces, controls should be placed within the reach of an operator's arm or foot for guaranteeing effective performance. In designing a workplace which must cater to a wide range of operator size, it might be sufficient to plan only for the ‘average person’. Static arm reach measurements which are taken in conventional, standardized positions provide necessary information, but they cannot be applied to dynamic situations directly. To obtain reach envelope or workspace of the human body not by direct measurement but by analytic generation, data on range of joint motion(ROM) are required as an input. The purposes of this research are to measure the range of motion of two degrees of freedom for Korean young males, and to propose an approximate algorithm to generate the workspace of the human body including foot and trunk motion, in which joint mobility of two degrees of freedom motion are considered. The robot kinematics was employed to represent the human body as a multi-link system.     

A spoken language interface with a mobile robot

We describe a spoken dialogue interface with a mobile robot, which a human can direct to specific locations, ask for information about its status, and supply information about its environment. The robot uses an internal map for navigation, and communicates its current orientation and accessible locations to the dialogue system. In this article, we focus on linguistic and inferential aspects of the human–robot communication process. This work was conducted at ICCS, School of Informatics, University of Edinburgh, Edinburgh, Scotland, UK This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

Impedance control with on-line neural-network compensator for robot contact tasks

In this paper, a force-tracking impedance controller with an on-line neural-network compensator is shown to be able to track a reference force in the presence of unknown environmental dynamics. The controller can be partitioned into three parts. The computed torque method is used to linearize and decouple the dynamics of a manipulator. An impedance controller is then added to regulate the mechanical impedance between the manipulator and its environment. In order to track a reference force signal, an on-line neural network is used to compensate the effect of unknown parameters of the manipulator and environment.     

Development of wheel-less snake robot with two distinct gaits and gait transition capability

Snake robots are mostly designed based on single mode locomotion. However, single mode gait most likely could not work effectively when the robot is subject to an unstructured working environment with different measures of terrain complexity. As a solution, mixed mode locomotion is proposed in this paper by synchronizing two types of gaits known as serpentine and wriggler gaits used for non-constricted and narrow space environments, respectively, but for straight line locomotion only. A gait transition algorithm is developed to efficiently change the gait from one to another. This study includes the investigation on kinematics analysis followed by dynamics analysis while considering related structural constraints for both gaits. The approach utilizes the speed of the serpentine gait for open area locomotion and exploits the narrow space access capability of the wriggler gait. Hence, it can increase motion flexibility in view of the fact that the robot is able to change its mode of locomotion according to the working environment.     

A novel approach of mining strong jumping emerging patterns based on BSC-tree

It is a great challenge to discover strong jumping emerging patterns (SJEPs) from a high-dimensional dataset because of the huge pattern space. In this article, we propose a dynamically growing contrast pattern tree (DGCP-tree) structure to store grown patterns and their path codes arrays with 1-bit counts, which are from the constructed bit string compression tree. A method of mining SJEPs based on DGCP-tree is developed. In order to reduce the pattern search space, we introduce a novel pattern pruning method, which dramatically reduces non-minimal jumping emerging patterns (JEPs) during the mining process. Experiments are performed on three real cancer datasets and three datasets from the University of California, Irvine machine-learning repository. Compared with the well-known CP-tree method, the results show that the proposed method is substantially faster, able to handle higher-dimensional datasets and to prune more non-minimal JEPs.