Image-based visual servo control of aerial robotic systems using linear image features

An image-based "eye-in-hand" visual servo-control design is proposed for underactuated rigid-body dynamics. The dynamic model considered is motivated by recent work on vertical takeoff and landing aerial robotic vehicles. The task considered is that of tracking parallel linear visual features. The proposed design exploits the geometry of the task considered and passivity-like properties of rigid-body dynamics to derive a control Lyapunov function using backstepping techniques.     

Crop recognition under weedy conditions based on 3D imaging for robotic weed control

A 3D time‐of‐flight camera was applied to develop a crop plant recognition system for broccoli and green bean plants under weedy conditions. The developed system overcame the previously unsolved problems caused by occluded canopy and illumination variation. An efficient noise filter was developed to remove the sparse noise points in 3D point cloud space. Both 2D and 3D features including the gradient of amplitude and depth image, surface curvature, amplitude percentile index, normal direction, and neighbor point count in 3D space were extracted and found effective for recognizing these two types of plants. Separate segmentation algorithms were developed for each of the broccoli and green bean plant in accordance with their 3D geometry and 2D amplitude characteristics. Under the experimental condition where the crops were heavily infested by various types of weed plants, detection rates over 88.3% and 91.2% were achieved for broccoli and green bean plant leaves, respectively. Additionally, the crop plants were segmented out with nearly complete shape. Moreover, the algorithms were computationally optimized, resulting in an image processing speed of over 30 frames per second.     

A three-dimensional statistical framework for performance measurement of robotic systems

A three-dimensional statistical evaluation framework for performance measurement of robotic systems has been developed. A specific experimental setup has been designed, implemented, and evaluated for different robot characteristics (velocities and target location) and for a specific task. A statistical analysis method to evaluate performance is demonstrated. Results indicate the significance of this methodology since the capabilities and performance of a particular robot depend on actual operating conditions.     

Learning control in robotic systems

The concept of learning and training machines, and some early methodologies were introduced about two decades ago. Robotic systems, undoubtedly, can be developed to a more advanced and intelligent stage. The realization of the learning capability, analogous to the human learning and thinking process, is a desired primary function. A betterment process has been investigated in the literature for applications of learning control to robotic systems. The existing schemes are a type of one-step learning process. A neighboring (2m+1)-step learning control scheme for robotic systems is presented in this paper. For each process, a betterment algorithm which chooses a generalized momentum as an output function, is executed. Also, it is associated with a conceptual learning process by adding a self-teaching knowledge base for speeding up the convergence, so that the learning capability of the resulting robotic systems can be enhanced.     

The null-space-based behavioral control for autonomous robotic systems

In this paper a new behavior-based approach for the control of autonomous robotic systems is proposed. The so-called null-space-based behavioral (NSB) control differs from the other existing methods in the behavioral coordination, i.e., in the way the outputs of the single elementary behaviors are combined to compose a complex behavior. The proposed approach is compared with the main existing approaches while two experimental case studies, performed with a Khepera II mobile robot, are reported to validate its effectiveness.     

Image-based control for cable-based robots

Some human robot interactive applications involved in tele-robotics, remote supervisory and unmanned systems require specific capabilities. This demand has promoted various interactive modes and high-level control techniques such as tele-manipulation, speech, vision, gesture, etc. Among these interactive modes, the image based control which is often named point and click control has proven to be the most appropriate one that offers multiple advantages. This mode consists of only and simply pointing in an appearing object of an image received from a remote site, to convert this click into a robot command towards the corresponding location in the real world space. This mode is suitable for remote applications, frees the human operator from being involved into the loop enabling him/her to use commands in the sense of click and forget. This paper presents, firstly, the design and the realization of an experimental planar cable-based robot constituted of four cables. Secondly, it presents the design and the implementation of a high-level image-based control. Some typical experiments which have been performed prove the simplicity and the effectiveness of the image-based control. Moreover, it opens perspectives for new applications with cable-based robots, particularity for rehabilitation applications.     

Direct adaptive control of robotic systems

This paper presents a new approach to adaptive motion control of an important class of robotic systems. The control schemes developed using this approach are very simple and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the robotic system dynamics. It is shown that the control strategies are globally stable in the presence of bounded disturbances, and that the size of the tracking errors can be made arbitrarily small. The proposed controllers are very general and are implementable with a wide variety of robotic systems, including both open- and closed-kinematic-chain manipulators. Computer simulation results are given for a seven degree-of-freedom (DOF) Robotics Research Corporation Model K-1607 arm. These results demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed schemes.     

Adaptive control of nonholonomic robotic systems

This paper considers the problem of controlling the motion of nonholonomic robotic systems in the presence of uncertainty regarding the system model and state, and presents a class of adaptive controllers as a solution to this problem. The proposed control strategies provide simple and robust solutions to a number of important nonholonomic system control problems, including stabilization to an equilibrium manifold, motion control to an equilibrium point via trajectory tracking, and stabilization to an equilibrium point. All of the schemes are computationally efficient, are implementable without knowledge of the system dynamic model, and ensure uniform boundedness of all signals and accurate motion control; furthermore, most of the controllers can be implemented without rate measurements. The efficacy of the proposed approach is illustrated through extensive computer simulations with nonholonomic robotic systems arising from explicit constraints on the system kinematics and from symmetries of the system dynamics. © 1998 John Wiley & Sons, Inc.     

不确定性机器人系统自适应鲁棒迭代学习控制

利用Lyapunov方法, 提出了一种不确定性机器人系统的自适应鲁棒迭代学习控制策略, 整个系统在迭代域里是全局渐近稳定的. 所考虑的机器人系统同时包含了结构和非结构不确定性. 在设计时, 系统的不确定性被分解成可重复性和非重复性两部分, 并考虑了系统的标称模型. 在所提出的控制策略中, 自适应策略用来估算做法确定性的界, 界的修正与迭代学习控制量一样的迭代域得以实现的. 计算机仿真表明本文提出的控制策略是有效的.     

Wave-variable framework for networked robotic systems with time delays and packet losses

This paper investigates the problem of networked control system for nonlinear robotic manipulators under time delays and packet loss by using passivity technique. With the utilisation of wave variables and a passive remote controller, the networked robotic system is demonstrated to be stable with guaranteed position regulation. For the input/output signals of robotic systems, a discretisation block is exploited to convert continuous-time signals to discrete-time signals, and vice versa. Subsequently, we propose a packet management, called wave-variable modulation, to cope with the proposed networked robotic system under time delays and packet losses. Numerical examples and experimental results are presented to demonstrate the performance of the proposed wave-variable-based networked robotic systems.     

Image-based truss recognition for density-based topology optimization approach

Structural and Multidisciplinary Optimization - Topology optimization is a tool that supports the creativity of structural-designers and is used in various industries, from automotive to...     

An impulsive dynamical systems framework for reset control systems

Impulsive dynamical systems is a well-established area of dynamical systems theory, and it is used in this work to analyse several basic properties of reset control systems: existence and uniqueness of solutions, and continuous dependence on the initial condition (well-posedness). The work scope is about reset control systems with a linear and time-invariant base system, and a zero-crossing resetting law. A necessary and sufficient condition for existence and uniqueness of solutions, based on the well-posedness of reset instants, is developed. As a result, it is shown that reset control systems (with strictly proper plants) do not have Zeno solutions. It is also shown that full reset and partial reset (with a special structure) always produce well-posed reset instants. Moreover, a definition of continuous dependence on the initial condition is developed, and also a sufficient condition for reset control systems to satisfy that property. Finally, this property is used to analyse sensitivity of reset control systems to sensor noise. This work also includes a number of illustrative examples motivating the key concepts and main results.     

Classical framework for nonholonomic mechanical control systems

With this paper we recall some of the formal framework developed in classical analytical mechanics with emphasis on constrained systems. It can be used in describing nonholonomic control systems and serve as a starting point for further differential-geometric investigations.     

Modified transpose Jacobian control of robotic systems

The simplicity of Transpose Jacobian (TJ) control is a significant characteristic of this algorithm for controlling robotic manipulators. Nevertheless, a poor performance may result in tracking of fast trajectories, since it is not dynamics-based. Use of high gains can deteriorate performance seriously in the presence of feedback measurement noise. Another drawback is that there is no prescribed method of selecting its control gains. In this paper, based on feedback linearization approach a Modified TJ (MTJ) algorithm is presented which employs stored data of the control command in the previous time step, as a learning tool to yield improved performance. The gains of this new algorithm can be selected systematically, and do not need to be large, hence the noise rejection characteristics of the algorithm are improved. Based on Lyapunov's theorems, it is shown that both the standard and the MTJ algorithms are asymptotically stable. Analysis of the required computational effort reveals the efficiency of the proposed MTJ law compared to the Model-based algorithms. Simulation results are presented which compare tracking performance of the MTJ algorithm to that of the TJ and Model-Based algorithms in various tasks. Results of these simulations show that performance of the new MTJ algorithm is comparable to that of Computed Torque algorithms, without requiring a priori knowledge of plant dynamics, and with reduced computational burden. Therefore, the proposed algorithm is well suited to most industrial applications where simple efficient algorithms are more appropriate than complicated theoretical ones with massive computational burden.     

Kinematic control of redundant free-floating robotic systems

This paper is aimed at presenting solution algorithms to the inverse kinematics of a space manipulator mounted on a free-floating spacecraft. The reaction effects of the manipulator's motion on the spacecraft are taken into account by means of the so-called generalized Jacobian. Redundancy of the system with respect to the number of task variables for spacecraft attitude and manipulator end-effector pose is considered. Also, the problem of both spacecraft attitude and end-effector orientation representation is tackled by means of a non-minimal singularity-free representation: the unit quaternion. Depending on the nature of the task for the spacecraft/manipulator system, a number of closed-loop inverse kinematics algorithms are proposed. Case studies are developed for a system of a spacecraft with a six-joint manipulator attached.     

Composite hierarchical anti-disturbance control for robotic systems with multiple disturbances

Various sources of disturbances exist simultaneously in robotic systems, such as vibrations, frictions, measurement noises, and equivalent disturbances from unmodeled dynamics and nonlinearities. However, most results on anti-disturbance control focus on only one type of disturbances, which cannot reflect the real applications and may lead to design conservativeness due to partial use of the disturbance information. In this paper, we propose a composite hierarchical anti-disturbance control (CHADC) strategy for robotic systems in the presence of multiple disturbances as well as system uncertainties. Particularly, we assume the existence of two types of disturbances, where the first type represents disturbances from exogenous systems with model perturbations, while the second type includes other random disturbances satisfying the L2-norm bound condition. Accordingly, the CHADC control architecture is composed of a nonlinear disturbance observer (NDO) and an H _∞ based PID controller, where the NDO is constructed to estimate the first type of disturbances and provide feed forward compensation, while the feedback PID loop is optimized using H _∞ theory to minimize the second type of disturbances. Robustness against system uncertainties is also considered in this hierarchical control structure. The proposed control approach is applied to a two-link robotic manipulator and compared with the conventional DOBC (disturbance observer based control) strategies.     

Intelligent agent based framework for manufacturing systems control

Existing modeling frameworks for manufacturing system control can be classified into hierarchical, heterarchical, and hybrid control frameworks. The main drawbacks of existing frameworks are discussed in this paper. A new hybrid modeling framework is also described. It is a hybrid of the two: hierarchical and heterarchical frameworks. In this proposed framework, entities (e.g., parts) and resources (e.g., material handling devices, machines, cells, departments) are modeled as holonic structures that use intelligent agents to function in a cooperative manner so as to accomplish individual, as well as cell-wide and system-wide objectives. To overcome the structural rigidity and lack of flexibility, negotiation mechanisms for real-time task allocation are used. Lower-level holons may autonomously make their negotiations within the boundary conditions that the higher-level holons set. Horizontal, as well as vertical decisions, are made between various levels of controllers, and these are explicitly captured in the model.     

A framework for meta-level control in multi-agent systems

Sophisticated agents operating in open environments must make decisions that efficiently trade off the use of their limited resources between dynamic deliberative actions and domain actions. This is the meta-level control problem for agents operating in resource-bounded multi-agent environments. Control activities involve decisions on when to invoke and the amount to effort to put into scheduling and coordination of domain activities. The focus of this paper is how to make effective meta-level control decisions. We show that meta-level control with bounded computational overhead allows complex agents to solve problems more efficiently than current approaches in dynamic open multi-agent environments. The meta-level control approach that we present is based on the decision-theoretic use of an abstract representation of the agent state. This abstraction concisely captures critical information necessary for decision making while bounding the cost of meta-level control and is appropriate for use in automatically learning the meta-level control policies.     

An integrated framework for card-based production control systems

Although card-based control systems, such as Kanban and CONWIP, for production processes have been successfully employed, the design discipline does not seem to be clear yet. Therefore, the superiority of one control over the other is controversial. This paper proposes a novel design discipline for card-based control of production processes, by developing the theory of token transaction systems. The theory shows how the three indices represented in Little??s law are decided by the structure of a production process with control cards and deployment of work-in-process (WIP). That is, the relation of WIP, cycle time and throughput on specific sub-network of a production process is clarified. We show how Little??s law should be used in the design of card-based production control systems. As an application of the theory, we resolve complicated result of comparison between Kanban and CONWIP. In doing so, this theory does not restrict the target of analysis to serial production lines, but any shaped processes can be analyzed.