Dynamic modeling and control for aerial arm-operating of a multi-propeller multifunction aerial robot

We proposed a multi-propeller multifunction aerial robot that is constructed by a quadrotor with two multi-DOF arms to enable aerial robotic operations. This paper addresses the dynamics and control problems for aerial arm-operation. The dynamic modeling considering the coupling between the arms and main-body subsystems is investigated using the Lagrange approach. The dynamics of the system are partitioned into the main-body dynamics, the arm dynamics, and the interaction dynamics. A composite controller consisting of a main-body sub-controller and an arm sub-controller are presented. Each sub-controller is designed based on the partitioned dynamics. The main-body sub-controller is designed using trajectory linearization control technique. This composite controller is appropriate for real-time implementation due to its simplicity. An optimal planning strategy that minimizes the interaction between main-body subsystem and arm subsystem is proposed. Experimental results are presented, verifying the effectiveness of the composite controller.     

Optimal custom design of both symmetric and unsymmetrical hexapod robots for aeronautics applications

The Stewart parallel mechanism is used in various applications due to its high load-carrying capacity, accuracy and stiffness, such as flight simulation, spaceship aligning, radar and satellite antenna orientation, rehabilitation applications, parallel machine tools. However, the use of such parallel robots is not widespread due to three factors: the limited workspace, the singularity configurations existing inside the workspace, and the high cost. In this work, an approach to support the design of a cost-effective Stewart platform-based mechanism for specific applications and to facilitate the choice of suitable components (e.g., linear actuators and base and mobile plates) is presented. The optimal design proposed in this work has multiple objectives. In detail, it intends to maximize the payload and minimize the forces at each leg needed to counteract external forces applied to the mobile platform during positioning or manufacturing, or, in general, during specific applications. The approach also aims at avoiding reduction of the robot workspace through a kinematic optimization. Both symmetric and unsymmetrical geometries have been analysed to show how the optimal design approach can lead to effective results with different robot configurations. Moreover, these objectives are achieved through a dynamic optimization and several optimization algorithms were compared in terms of defined performance indexes.     

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.     

Ｓｔｅｗａｒｔ主动隔振平台的神经网络自适应控制

针对Stewart主动隔振平台,提出一种基于径向基函数(RBF)神经网络的多输入多输出自适应隔振控制方法.考虑外界振动对Stewart主动隔振平台动态特性的影响,建立了隔振平台在工作空间中的动力学模型.推导出RBF神经网络的权值矩阵、高斯基函数中心和宽度的在线自适应调节律,以使神经网络快速逼近系统的非线性动态函数.应用Lyapunov稳定性理论,证明了在扰动力和神经网络逼近误差有界的条件下,闭环控制系统滤波误差和RBF神经网络各调节参数估计误差的一致最终有界.仿真结果表明,该控制方法能有效地抑制不同方向的低频有界振动.     

Dynamic optimal payload path planning of mobile manipulators among moving obstacles

This paper is dealt with dynamic analysis of the wheeled mobile manipulators in the presence of moving obstacles considering optimal payload criterion. General dynamic formulation of the system was derived, and the moving obstacle avoidance strategy was proposed in terms of dynamic potential functions. The problem of dynamic motion planning and payload maximization was formulated using open-loop optimal control theory. Then, the indirect solution based on Pontryagin’s minimum principle was employed to solve the problem. Using the proposed method, complete nonlinear states and control constraints were treated without any simplifications such as linearizing the dynamics equations, discretizing the robot’s workspace, or parameterizing the solution. The proposed method will be useful for the system design and in the situation where the trajectories of obstacles are predefined. Finally, capability and applicability of the proposed method were investigated by the number of simulations on a two-link mobile manipulator.     

受约束空间机器人降阶自适应神经网络滑模控制

为了实现受约束空间机器人的高精度控制,提出了一种基于U-K(Udwadia-Kalaba)方程的降阶自适应神经网络滑模控制算法;基于U-K方程,同时考虑受约束空间机器人各个关节的理想约束力与非理想约束力,推导得到详细的动力学方程;考虑到非理想约束力具有不确定性且单独采用滑模控制会出现抖振现象,提出了自适应神经网络滑模控制算法,实现各关节角度、角速度以及非理想约束力的高精度跟踪;针对系统受约束模型,对动力学方程和滑模控制器进行了降阶求解,减少了变量并简化了计算过程;为了验证所提算法的正确性与合理性,以2自由度受约束空间机器人为例进行了仿真验证;仿真结果表明：受约束空间机器人的各关节角度、角速度以及非理想约束力的跟踪误差均低于10^-4量级。     

Maximum DLCC of Spatial Cable Robot for a Predefined Trajectory Within the Workspace Using Closed Loop Optimal Control Approach

One of the most important applications of cable robots is load carrying along a specific path. Control procedure of cable robots is more challenging compared to linkage robots since cables can’t afford pressure. Meanwhile carrying the heaviest possible payload for this kind of robots is desired. In this paper a nonlinear optimal control is proposed in order to control the end-effector within a predefined trajectory while the highest Dynamic Load Carrying Capacity (DLCC) can be carried. This purpose is met by applying optimum torque distribution among the motors with acceptable tracking accuracy. Besides, other algorithms are applied to make sure that the allowable workspace constraint is also satisfied. Since the dynamics of the robot is nonlinear, feedback linearization approach is employed in order to control the end-effector on its desirable path in a closed loop way while Linear Quadratic Regulator (LOR) method is used in order to optimize its controlling gains since the state space is linearized by the feedback linearization. The proposed algorithm is supported by doing some simulation studies on a two Degrees of Freedom (DOF) constrained planar cable robot as well as a six DOFs under constrained cable suspended robot and their DLCCs are calculated by satisfying the motor torque, tracking error and allowable workspace constraints. The results including the angular velocity, motors’ torque, actual tracking of the end-effector and the DLCC of the robot are calculated and verified using experimental tests done on the cable robot. Comparison of the results of open loop simulation results, closed loop simulation results and experimental tests, shows that the results are improved by applying the proposed algorithm. This is the result of tuning the motors’ torque and accuracy in a way that the highest DLCC can be achieved.     

A Simple and Novel Hybrid Robotic System for Robot-Assisted Femur Fracture Reduction

When performing femur fracture reduction surgery, both the patient and surgeon are exposed to a great amount of radiation, which is harmful to their health. In order to reduce such radiation from the usage of an image intensifier, various robots have been proposed for femur fracture reduction surgery. Most of these robots are based on serial architecture. The low transportable load and poor accuracy are both inherent in serial robots, which makes them inappropriate for femur fracture reduction. Some parallel robots based on the 'Stewart platform' have also been developed for femur fracture reduction, but their restricted workspace limits their applicability and accessibility. To balance the accuracy, payload and workspace, a new robot system is reported in this paper. The proposed robot system consists of a 2-d.o.f. device and a 6-d.o.f. hybrid robot. The 2-d.o.f. device is used for distraction, which requires a very large force. The hybrid robot is used to manipulate a bone fragment for alignment and fixation purposes. The hybrid robot possesses the characteristic of a Cartesian coordinate robot; all the movements of the actuators are linear, which makes its motion smooth for low-speed fracture reduction procedures. The forward and inverse kinematics of the proposed robot are analyzed. The analysis is much simpler compared to traditional serial manipulators and parallel Stewart platform robots. A prototype of the proposed system is made using a rapid fabrication system called Objet. The positioning accuracy of the proposed system is measured using a coordinate-measuring machine. The results show that the algorithms presented in this paper for the control of the robot are accurate and robust.     

空间站载荷转移机构机器人的力加载控制方法

针对机器人在空间站载荷转移机构力加载过程中,由于展开完成后的载荷转移机构在力的方向上发生变形,导致机器人力控制系统难以保持稳定、加载精度不足或调节时间过长的问题,提出了自适应调整导纳控制器参数的策略．首先,根据导纳控制理论建立力与位移的关系,初步提出了基于直角坐标系的力跟随/力加载控制器;然后,根据加载实验数据,采用最小二乘法对载荷转移机构模型进行参数辨识,建立机器人特定工作空间的力与位置关系;最后,通过自适应调整导纳控制器参数使机器人动力学模型与载荷转移机构的动力学模型近似匹配,实现机器人对展开完成后的载荷转移机构末端的空间力实时加载．实验得出机器人对载荷转移机构位置跟随偏差不超过0.1 mm,加载力误差不超过1%．仿真结果表明,该机器人满足精度要求,为载荷转移机构提供了较为真实的等效空间载荷．     

Decoupling control for spatial six-degree-of-freedom electro-hydraulic parallel robot

This paper presents a decoupling controller equipped with cross-coupling pre-compensation for an electro-hydraulic parallel robot, in order to weaken system dynamic coupling effects usually ignored on the design of advanced controllers and improve system control performance. The mathematical model of the electro-hydraulic parallel robot is built using the Kane method and a hydromechanics approach, and the kinematical model is established with a closed-form solution and the Newton-Raphson method. The feedback linearization theory is applied to reduce coupling effects stemmed from system dynamics of the parallel robot via incorporating force-velocity control with cross-coupling pre-compensations. The control performance involving stability, accuracy, and robustness of the proposed controller for spatial 6-DOF parallel robot is analyzed in theory and experiment. The experimental results illustrate that the proposed controller can highly improve the control performance by weakening system dynamic coupling effects of the electro-hydraulic parallel robot, especially for trajectory tracking performance.     

Cooperative Control of a 3D Dual-Flexible-Arm Robot

This paper discusses cooperative control of a dual-flexible-arm robot to handle a rigid object in three-dimensional space. The proposed control scheme integrates hybrid position/force control and vibration suppression control. To derive the control scheme, kinematics and dynamics of the robot when it forms a closed kinematic chain is discussed. Kinematics is described using workspace force, velocity and position vectors, and hybrid position/force control is extended from that on dual-rigid-arm robots. Dynamics is derived from constraint conditions and the lumped-mass-spring model of the flexible robots and an object. The vibration suppression control is calculated from the deflections of the flexible links and the dynamics. Experiments on cooperative control are performed. The absolute positions/orientations and internal forces/moments are controlled using the robot, each arm of which has two flexible links, seven joints and a force/torque sensor. The results illustrate that the robot handled the rigid object damping links' vibration successfully in three-dimensional space.     

A Telepresence-Guaranteed Control Scheme for Teleoperation Applications of Transferring Weight-Unknown Objects

Currently, most teleoperation work is focusing on scenarios where slave robots interact with unknown environments. However, in some fields such as medical robots or rescue robots, the other typical teleoperation application is precise object transportation. Generally, the object’s weight is unknown yet essential for both accurate control of the slave robot and intuitive perception of the human operator. However, due to high cost and limited installation space, it is unreliable to employ a force sensor to directly measure the weight. Therefore, in this paper, a control scheme free of force sensor is proposed for teleoperation robots to transfer a weight-unknown object accurately. In this scheme, the workspace mapping between master and slave robot is firstly established, based on which, the operator can generate command trajectory on-line by operating the master robot. Then, a slave controller is designed to follow the master command closely and estimate the object’s weight rapidly, accurately and robust to unmodeled uncertainties. Finally, for the sake of telepresence, a master controller is designed to generate force feedback to reproduce the estimated weight of the object. In the end, comparative experiments show that the proposed scheme can achieve better control accuracy and telepresence, with accurate force feedback generated in only 500 ms.      

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler–Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.     

A neural network-based approach for an assembly cell control

In several robotics applications, the robot must interact with the workspace, and thus its motion is constrained by the task. In this case, pure position control will be ineffective since forces appearing during the contacts must also be controlled. However, simultaneous position and force control called hybrid control is then required. Moreover, the nonlinear plant dynamics, the complexity of the dynamic parameters determination and computation constraints makes more difficult the synthesis of control laws. In order to satisfy all these constraints, an effective hybrid force/position approach based on artificial neural networks for multi-inputs/multi-outputs systems is proposed. This approach realizes, simultaneously, an identification and control of systems, and it is implemented according to two phases: At first, a neural observer is trained off-line on the basis of the data acquired during contact motion, in order to realize a smooth transition from free to contact motion. Then, an online learning of the neural controller is implemented using neural observer parameters so that the closed-loop system maintains a good performance and compensates for uncertain/unknown dynamics of the robot and the environment. A typical example on which we shall focus is an assembly task. Experimental results on a C5 links parallel robot demonstrate that the robot's skill improves effectively and the force control performances are satisfactory, even if the dynamics of the robot and the environment change.     

On the position analysis of a new spherical parallel robot with orientation applications

In this paper, we propose a new spherical parallel robot for celestial orientation, and rehabilitation applications (TV satellite dish, tracking systems, solar panels, cameras, telescopes, table of the machine tools, ankle, shoulder, wrist and etc.). The proposed robot can completely rotate about an axis. After describing the robot and its inverse position analysis, using the genetic algorithm, the dimensional optimization to maximize the workspace of the robot is performed. The workspace analysis shows that the proposed robot has a relatively large workspace. Also, singularity analysis represents that the manipulator is a singularity-free workspace. It is a great advantage of the proposed robot. Next, an optimal approach is proposed for solving the direct position problem of the robot. According to the geometry of the robot, two coupled trigonometric equations are obtained through using a special form of Rodrigues' rotation formula. Next, the two coupled equations are transformed to a 8-degrees polynomial using the Sylvester's Dialytic elimination method. Finally, a numerical example for the robot with an asymmetric structure is given with eight real solutions. Therefore, the polynomial being minimal and the proposed approach is optimal. This greatly decreases computational time, which is necessary for dynamics, control and simulation.     

Dynamic analysis and control of a stewart platform manipulator

The Stewart platform is a six-axis parallel robot manipulator with a force-to-weight ratio and positioning accuracy far exceeding that of a conventional serial-link arm. Its stiffness and accuracy approach that of a machine tool yet its workspace dexterity approaches that of a conventional manipulator. In this article, we study the dynamic equations of the Stewart platform manipulator. Our derivation is closed to that of Nguyen and Pooran because the dynamics are not explicitly given but are in a step-by-step algorithm. However, we give some insight into the structure and properties of these equations: We obtain compact expressions of some coefficients. These expressions should be interesting from a control point of view. A stiffness control scheme is designed for milling application. Some path-planning notions are discussed that take into account singularity positions and the required task. The objective is to make the milling station into a semiautonomous robotic tool needing some operator interaction but having some intelligence of its own. It should interface naturally with part delivery and other higher-level tasks.     

Direct adaptive impedance control of robot manipulators

This article presents an adaptive scheme for controlling the end-effector impedance of robot manipulators. The proposed control system consists of three subsystems: a simple “filter” that characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller that produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics and is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter. Computer simulation results are given for a planar four degree-of-freedom redundant robot under adaptive impedance control. These results demonstrate that accurate end-effector impedance control and effective redundancy utilization can be achieved simultaneously by using the proposed controller.     

3-DOF planar parallel-wire driven robot with an active balancer and its model-based adaptive control

This paper has proposed a parallel-wire driven robot (PWDR) with an active balancer, which is notably useful for such applications as ceiling maintenance and object conveyance near a ceiling in a factory. Because this robot is an under-actuated system, the uncertainty of the inertial parameters of the load strongly affects the resultant motion and reduces the control accuracy because of the dynamics interference. However, to date, the dynamics of this robot has not been thoroughly elucidated. Thus, this study analyzes the dynamics of a PWDR that controls three degree-of-freedom using two wires and an active balancer. Moreover, based on the dynamic analysis, a model-based adaptive controller for the parameter uncertainty of a load is proposed, and its effectiveness is demonstrated through simulation.     

Computer control of robotic manipulators using predictors

Model-based robot control algorithms require the on-line evaluation of robot dynamics, leading to hybrid continuous/discrete-time implementations. The performance of these fixed-gain control algorithms varies in the workspace and it is not adequate for trajectory-tracking. In this paper, we present a coherent discrete-time framework for the analysis of model-based algorithms and introduce predictors to compensate for modeling and discretization errors. The basic controller structure is not altered; an added supervisory module is proposed to monitor performance and adjust the command signal accordingly. The module injects a degree of adaptiveness in the controller and reduces the sensitivity of the design to unmodeled dynamics. Our preliminary simulation experiments confirm that one-step-ahead predictors lead to a more uniform performance and are suitable for trajectory-tracking applications.A preliminary version of this paper appeared in the Proceedings of the IEEE International Symposium on Intelligent Control, Philadelphia, Pennsylvania, 19–20 January 1987. Research supported in part by the National Science Foundation under Grant No. DMC-8707622.