Three-dimensional pursuer convoy by using guidance laws

This paper investigates the problem of modeling and controlling pursuer convoy in three-dimensional space. The guidance laws applied for convoy, the velocity pursuit, the deviated pursuit and the proportional navigation, steer the pursuer using the rate of line-of-sight (LOS) between successive pursuers. On the basis of the differential equations for the range, the pitch angle of LOS and the yaw angle of LOS between successive pursuers, the guidance laws are proposed to derive decentralized control strategy for pursuer convoy. The results concerning the pursuer convoy are rigorously proven. Simulations are conducted to demonstrate the feasibility and effectiveness of the proposed control strategy.     

A biological neuroprocessor for robotic guidance using a center of area method

This paper introduces a neuroinformatic system using human neuroblastoma cultures and centre of area learning for basic robotic guidance. Multielectrode Arrays Setups have been designed for direct culturing neural cells over silicon or glass substrates, providing the capability to stimulate and record simultaneously populations of neural cells. The main objective of this work will be to control a robot using this biological neuroprocessor and a simple centre of area learning scheme. The final system could be applied for testing how chemicals affect the behaviour of the robot or to establish the basis for new hybrid optogenetic learning.     

Development of guidance laws for a variable-speed missile

The most used guidance law for short-range homing missiles is proportional navigation (PN). In PN, the acceleration command is proportional to the line-of-sight (LOS) angular velocity. Indeed, if a missile and a target move on a collision course with constant speeds, the LOS rate is zero. The speed of a highly maneuverable modem missile varies considerably during flight. The performance of PN is far from being satisfactory in that case.In this article we analyze the collision course for a variable-speed missile and define a guidance law that steers the heading of the missile to the collision course. We develop guidance laws based on optimal control and differential game formulations, and note that both optimal laws coincide with the Guidance to Collision law at impact. The performance improvement of the missile using the new guidance law as compared to PN is demonstrated.Recommended by A.W. Merz     

Operational learning with sensory feedback for controlling a robotic thumb using the posterior auricular muscle

Extra robotic limbs in a robotic system that are designed to augment and expand human abilities have received attention in the field of wearable robotics. We aim to develop a robotic system that is controlled by body parts that are not used on a daily basis in order to augment and expand human abilities. This paper presents operational learning experiments for manipulating a robotic thumb using the posterior auricular muscle, a body part that is not used in everyday life. In these experiments, reaching motions were executed using sensory feedback in the robotic thumb through a device that continuously displays its position. The experimental results indicate the proposed operational learning experiments improve the ability to contract the posterior auricular muscles. In addition, the results indicate the operability of a robotic thumb could be improved by acquiring internal models through repetitive operational learning.     

Design of midcourse guidance laws via a combination of fuzzy and SMC approaches

Issues regarding the design of midcourse guidance laws for antimissiles are addressed. The antimissile is expected to be guided to a place with a desired direction, where a ballistic missile is predicted to pass in the reverse direction, so that the target can be easily found and locked for terminal interception. The predicted location and direction of a ballistic missile may vary with time, due to information update using a trajectory prediction algorithm. To fulfill the guidance performance, the guidance laws are designed by combining the Takagi-Sugeno (T-S) fuzzy approach and the Sliding Mode Control (SMC) technique. Under the designed guidance law, it is shown that the antimissile is able to be efficiently guided to a specified location and direction, even when the existence of uncertainties and disturbances.     

Movement time and guidance accuracy in teleoperation of robotic vehicles

Two experiments are reported on the steering of a tracked vehicle through straight-line courses and corners to determine the relationships between movement time and control accuracy with the geometry of the course, such as the vehicle width, the track width and the type of corner. For straight line tracking, Drury’s law in which movement time (MT) is linear with the tracking task difficulty measure [A/(W???d)] is found to hold, where A is the distance traveled, ‘W’ is the track width and ‘d’ is the vehicle width. Performance in three types of corners (right angle, cut angle and circular) varied little, with the most important factor being the clearance (W???d) available to the operator. Collisions with boundary walls were also highly related to this factor. The reported research has strong relevance to the training of operators for urban search and rescue robots.

Practitioner summary: Data for steering a real vehicle in a simulated environment of straight paths and different corner geometries showed that Drury’s law holds for straight line tracking and the clearance between the widths of vehicle and track is important in steering corners. Data show clear need for training of USAR (Urban Search and Rescue) operators.     

Modeling of a scanning laser range sensor for robotic applications

The geometric and noise modeling of a scanning range sensor is described. The parameters of the model are determined from data collected during the calibration of the real sensor. The models are shown to predict range scan results which accurately match those of the real sensor.     

Towards a robotic plasma spraying operation using vision

An uncalibrated, vision-guided robotic system, based on the method of camera-space manipulation, has been developed to reduce the time and cost associated with teaching a robot a suitable trajectory for plasma coating. The system achieves a high level of precision in both position and orientation control of a 6-DOF robotic arm     

A novel method for coevolving PS-optimizing negotiation strategies using improved diversity controlling EDAs

In agent-mediated negotiation systems, the majority of the research focused on finding negotiation strategies for optimizing price only. However, in negotiation systems with time constraints (e.g., resource negotiations for Grid and Cloud computing), it is crucial to optimize either or both price and negotiation speed based on preferences of participants for improving efficiency and increasing utilization. To this end, this work presents the design and implementation of negotiation agents that can optimize both price and negotiation speed (for the given preference settings of these parameters) under a negotiation setting of complete information. Then, to support negotiations with incomplete information, this work deals with the problem of finding effective negotiation strategies of agents by using coevolutionary learning, which results in optimal negotiation outcomes. In the coevolutionary learning method used here, two types of estimation of distribution algorithms (EDAs) such as conventional EDAs (S-EDAs) and novel improved dynamic diversity controlling EDAs (ID²C-EDAs) were adopted for comparative studies. A series of experiments were conducted to evaluate the performance for coevolving effective negotiation strategies using the EDAs. In the experiments, each agent adopts three representative preference criteria: (1) placing more emphasis on optimizing more price, (2) placing equal emphasis on optimizing exact price and speed and (3) placing more emphasis on optimizing more speed. Experimental results demonstrate the effectiveness of the coevolutionary learning adopting ID²C-EDAs because it generally coevolved effective converged negotiation strategies (close to the optimum) while the coevolutionary learning adopting S-EDAs often failed to coevolve such strategies within a reasonable number of generations.     

变量泵控制变量马达系统建模及控制

变量泵控制变量马达系统是一个双输入单输出耦合本质非线性系统, 常规控制方法很难取得满意的控制效果. 针对变量泵控制变量马达系统非线性和不可解耦的特点, 提出基于线性化理论的变量泵变量马达Bang-Bang控制算法. 首先建立变量泵控制变量马达系统数学模型, 模型存在包括输出变量在内的相乘非线性, 然后运用反馈线性化理论将非线性数学模型线性化, 最后提出新的Bang-Bang控制算法实现变量马达的快速控制.仿真研究表明该算法可以实现系统快速控制, 效果优于目前常规控制方法, 而且算法对马达转速和负载变化都具有较强的鲁棒性.     

Modeling interaction strategies using POS: An application to soccer robots

As seen earlier POS is a general agent conversation protocol engineering formalism that has proved efficient when used in communities of software information agents. The aim of this paper is to show how much POS is simple, easy to use, and very appropriate for implementing interaction protocols in a collaborative agent setting. In order to exemplify our approach we focus on an application domain with real time constraints such as soccer robots and show how an inherently symbolic abstract system like POS can be neatly integrated with agents whose internal architecture is reactive and relies on bottom-up behavior-based techniques. First, we shortly discuss aspects of heterogeneity with respect to soccer robots and present the RoboCup experimental setting. Then we sketch the difficulties that arise when trying to coordinate an heterogeneous team with conventional methods. In response, we introduce some elements of the POS (Protocol Operational Semantics) model. The following sections examine several basic behaviors of the JavaSoccer simulation environment as it is later used along with TeamBots to highlight POS’ capabilities, demonstrate how POS is a suited theoretical tool and leads to extremely compact and modular code due to its high expressive power, and discuss the obtained results. Finally we conclude the article with a comparison to related works as well as some perspectives about the engineering of interaction protocols.     

Automatic folding of cartons using a reconfigurable robotic system

This paper proposes new theories and methodology for the study of folding carton and reconfigurable packaging systems and presents both virtual and experimental systems to support the theories. Equivalent mechanisms of cartons were established by describing carton creases as joints and carton panels as links. With the analysis of the equivalent mechanism, the gusset vertexes of cartons were analyzed based on their equivalent spherical linkages and were identified as guiding linkages that determine folding. A reconfigurable robotic system was developed to demonstrate the ability to erect diverted cartons in the reconfigurable packaging system which could previously only be achieved manually.     

Nuclear sample management using a plutonium dissolution robotic system

At Los Alamos National Laboratory, a unique sample management robotic system has been developed that automates plutonium metal acid dissolutions, the aliquoting of resulting solutions to be analyzed using several analytical chemistry methods, and automates the barcode labeling of the solution containment vial providing positive solution identification. This system is based upon a commercial laboratory robot from Zymark, Inc. that has been enhanced by the addition of custom robotic workstations engineered and fabricated at our facility. This system will significantly reduce personnel radiation exposure and eliminate the redundancy of each analytical area producing separate dissolved plutonium solutions, which are used in chemical analyses.     

Modeling and intellligent chatter control strategies for a lathe machine

In the active chatter control of machine tools, the most effective way to suppress the chatter is to place the actuator as close as possible to the tool tip. However, in practice, it is almost impossible to put the actuator at the same location of the tool tip. Also, in many machines the cutting tools are usually long and may be flexible. Both of these problems pose serious problems in machine chatter control. In order to control the chatter effectively and efficiently, a systematic methodology is proposed in this paper to deal with the modeling and control system design aspects of this challenging problem. Because of the flexibility effect in the tool shaft, conventional active control approaches may not perform in an efficient and effective manner. Here, two advanced control algorithms (LMS adaptive filter and fuzzy CMAC neural network) are proposed to counteract this problem. Experimental results on a lathe machine are also included. Approximately 20 dB reduction in chatter has been achieved.     

A novel actuation for a robotic fish using a flexible joint

This paper presents a novel actuation mechanism to enable the span-wise undulating motion of the caudal fin of a robotic fish. To minimize the mechanical components such as cams, pulleys and gears, a flexible joint-based wave machine mechanism is adopted to generate the waving motion of the caudal fin. In particular, the proposed mechanism has the advantages of minimum total weight and few mechanical components because of its simplicity. Through analysis and experiments, the efficacy of the proposed mechanism is validated.     

Autonomous robotic inspection and manipulation using multisensorfeedback

A six-degree-of-freedom industrial robot to which was added a number of sensors-vision, range, sound, proximity, force/torque, and touch-to enhance its inspection and manipulation capabilities is described. The work falls under the scope of partial autonomy. In teleoperation mode, the human operator prepares the robotic system to perform the desired task. Using its sensory cues, the system maps the workspace and performs its operations in a fully autonomous mode. Finally, the system reports back to the human operator on the success or failure of the task and resumes its teleoperation mode. The feasibility of realistic autonomous robotic inspection and manipulation tasks using multisensory information cues is demonstrated. The focus is on the estimation of the three-dimensional position and orientation of the task panel and the use of other nonvision sensors for valve manipulation. The experiment illustrates the need for multisensory information to accomplish complex, autonomous robotic inspection and manipulation tasks     

Modeling and design of a humanoid robotic face based on an active drive points model

This study develops a face robot with human-like appearance for making facial expressions similar to a specific subject. First, an active drive points (ADPs) model is proposed for establishing a robotic face with less active degree of freedom for bipedal humanoid robots. Then, a robotic face design method is proposed, with the robot possessing similar facial appearance and expressions to that of a human subject. A similarity evaluation method is presented to evaluate the similarity of facial expressions between a robot and a specific human subject. Finally, the proposed facial model and the design methods are verified and implemented on a humanoid robot platform.     

Modeling, analysis, and performance evaluation of a robotic grippersystem for limp material handling

This paper presents an analytical model of a flat surfaced robotic gripper designed to automate the process of reliable, rapid and distortion-free limp material handling. The designed gripper prototype is integrated with an industrial robot manipulator. The gripper geometry and its grasp stability are justified. Performance of the overall system is experimentally tested, based on a set of industry dictated operational constraints. It is found that the gripper system has high reliability, grasp stability, and that it is capable of rapid rates of manipulation.     

Improved nonlinear trajectory tracking using RBFNN for a robotic helicopter

This paper presents a backstepping control method using radial‐basis‐function neural network (RBFNN) for improving trajectory tracking performance of a robotic helicopter. Many well‐known nonlinear controllers for robotic helicopters have been constructed based on the approximate dynamic model in which the coupling effect is neglected; their qualitative behavior must be further analyzed to ensure that the unmodeled dynamics do not destroy the stability of the closed‐loop system. In order to improve the controller design process, the proposed controller is developed based on the complete dynamic model of robotic helicopters by using an RBFNN function approximation to the neglected dynamic uncertainties, and then proving that all the trajectory tracking error variables are globally ultimately bounded and converge to a neighborhood of the origin. The merits of the proposal controller are exemplified by four numerical simulations, showing that the proposed controller outperforms a well‐known controller in (J. Robust Nonlinear Control 2004; 14 (12):1035–1059). Copyright © 2009 John Wiley & Sons, Ltd.     

Micro-gravity experiment of a space robotic arm using parabolic flight

We conducted a micro-gravity flight experiment on a space robotic arm, which is a part of the Reconfigurable Brachiating space Robot (RBR) unit arm developed by the authors. We used a 4-d.o.f. arm and an end-effector in the experiment. The airplane (MU-300) generates the micro-gravity environment for approximately 20 s in parabolic flight operation. After the flight, we conducted the corresponding ground experiments, and obtained the data of the motor current, servo control characteristics and manipulation performances, which were compared with the flight experiment data. Then, we conducted the numerical analysis of the 4-d.o.f. RBR arm based on the experiment results. In the analysis, we investigated feasibility of simulation model and identified model parameters. In this paper, we report the results of the flight experiments and numerical analysis.