机器人末端臂轨迹跟踪自适应控制设计

本文提出了新颖的机器人末端臂轨迹跟踪自适应控制方法。该方法与已有的神经网络模型不同之处在于数据首先利用运动学反解求出机器人各关节旋转的角度,然后应用径向基函数自组织进行神经网络学习生成模糊规则,利用监督学习算法(SLA)、最小二乘法(LMS)、反向传播算法(BP)和聚类分析的方法在线优化控制规则以及隶属函数的参数。仿真结果表明,该方法不但规则生成的时间少,有效的防止了规则数爆炸,而且在机器人轨迹跟踪控制的应用中效果好。     

On-line motion synthesis and adaptation using a trajectory database

Autonomous robots cannot be programmed in advance for all possible situations. Instead, they should be able to generalize the previously acquired knowledge to operate in new situations as they arise. A possible solution to the problem of generalization is to apply statistical methods that can generate useful robot responses in situations for which the robot has not been specifically instructed how to respond. In this paper we propose a methodology for the statistical generalization of the available sensorimotor knowledge in real-time. Example trajectories are generalized by applying Gaussian process regression, using the parameters describing a task as query points into the trajectory database. We show on real-world tasks that the proposed methodology can be integrated into a sensory feedback loop, where the generalization algorithm is applied in real-time to adapt robot motion to the perceived changes of the external world.     

Stabilization of translational-rotational motion of uniaxial wheeled platform along a linear trajectory

The problem of stabilization of a uniaxial wheeled platform with the property of being an upper inverted pendulum along a program trajectory is considered. Control problems for the center of mass of the platform and its stabilization about the center of mass in the horizontal and vertical planes are solved. The specific feature of constructed controls is their continuous correction based on application of analytical relations of wheel interaction with a ground surface for providing nonholonomic constraints for the wheels and the surface.     

An exoskeletal robot for human elbow motion support-sensor fusion,adaptation, and control

In order to help everyday life of physically weak people, we are developing exoskeletal robots for human (especially for physically weak people) motion support. In this paper, we propose a one degree-of-freedom (1 DOF) exoskeletal robot and its control system to support the human elbow motion. The proposed controller controls the angular position and impedance of the exoskeletal robot system based on biological signals that reflect the human subject's intention. The skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been fused and used as input information of the controller. In order to make the robot flexible enough to deal with vague biological signal such as EMG, fuzzy neuro control has been applied to the controller. The experimental results show the effectiveness of the proposed exoskeletal robot system.     

Torso motion control and toe trajectory generation of a trotting quadruped robot based on virtual model control

This article presents an intuitive approach based on virtual model control for robust quadrupedal trotting. The controller consists of two main modules: support phase virtual model control for torso motion control and flight phase virtual model control for flight toe trajectory generation. We mapped the relationship between the joint torques of support legs and the torso forces. And virtual forces are applied to the torso to regulate the attitude, height, and velocities of the torso during support phase. To unify the control law, virtual forces are also applied to flight toes to track the planned trajectories that are designed based on lateral velocity of the torso and contact signals of the legs. Moreover, state machine, terrain estimator, and the high level controller are designed to control the robot trotting. Simulations of quadruped trotting versatilely on flat ground, trotting over stairs and slops as well as the impact recovery are reported to demonstrate the effectiveness and robustness of our controller.     

Time-optimal and jerk-continuous trajectory planning for robot manipulators with kinematic constraints

In this paper a high smooth trajectory planning method is presented to improve the practical performance of tracking control for robot manipulators. The strategy is designed as a combination of the planning with multi-degree splines in Cartesian space and multi-degree B-splines in joint space. Following implementation, under the premise of precisely passing the via-points required, the cubic spline is used in Cartesian space planning to make either the velocities or the accelerations at the initial and ending moments controllable for the end effector. While the septuple B-spline is applied in joint space planning to make the velocities, accelerations and jerks bounded and continuous, with the initial and ending values of them configurable. In the meantime, minimum-time optimization problem is also discussed. Experimental results show that, the proposed approach is an effective solution to trajectory planning, with ensuring a both smooth and efficiency tracking performance with fluent movement for the robot manipulators.     

On the motion of a mobile robot with roller-carrying wheels

The motion equations of a robot on a horizontal surface on three roller-carrying wheels of omni directional type are derived without account of possible slippage. An exact solution of the equations is found when at the direct-current motors moving the wheels a constant voltage is supplied. The problem of minimizing the torques of electric motors is considered and steady-state motion modes are specified for which the torques of electric motors and energy expenses are minimum. The reckoning system for the robot traveled distance is described.     

Robust control of robot manipulators with fast load adaptation

Many adaptive robot controllers have been proposed in the literature to solve manipulator trajectory tracking problems for high-speed operations in the presence of parameter uncertainties. However, most of these controllers stem from the applications of the existing adaptive control theory, which is traditionally focused on tracking slowly time-varying parameters. In fact, manipulator dynamics have fast transient processes for high-speed operations and load changes are abrupt. These observations motivate the present research to incorporate change detection techniques into self-tuning schemes for tracking abrupt load variations and achieving fast load adaptation. To this end, a robustly global stabilizing controller for a robot model with parametric and non-parametric uncertainies is developed based on the Lyapunov second method, and it is then made adaptive via the self-tuning regulator concept. The two-model approach to online change detection in load is used and the estimation algorithm is reinitialized once load changes are detected. This allows a much faster adaptive identification of load parameters than the ordinary forgetting factor approach. Simulation results demonstrate that the proposed controller achieves better tracking accuracy than the existing adaptive and non-adaptive controllers.     

A control for an insectomorphic robot in motion along a vertical corner and a horizontal beam

The problems of climbing a vertical corner and of moving on a horizontal beam while maintaining dynamic balance are solved for a six-legged robot. The opening angle of the comer is equal to Gp/2, and robot climbs it from a horizontal supporting surface. The motion is implemented using dry friction forces. The motion pattern in the passage from the horizontal surface on the corner and the motion in the upward direction are determined by the structure of the gallop gait. Using computer simulation, it is shown that a friction coefficient equal to 1.1 is sufficient for implementation of the motion constructed. In the motion on a narrow beam, the robot goes by a diagonal gait on the front and back legs. The middle legs are used as fly wheels in order to control the kinetic moment of the body relative to the supporting diagonal to reach robot stability in the top position. A PD-controller is designed that provides the required control of the relative motion of the middle legs. The results of computer simulation of the controlled robot dynamics are presented.     

Adaptive trajectory tracking neural network control with robust compensator for robot manipulators

Neural Computing and Applications - This paper presents an adaptive trajectory tracking neural network control using radial basis function (RBF) for an n-link robot manipulator with robust...     

Energy-saving trajectory planning for an inverse ball drive robot with Mecanum wheels

International Journal of Control, Automation and Systems - This paper proposes a new energy-saving trajectory planning method for a robot with an inverse ball driven by Mecanum wheels. The slip due...     

Design of a large-scale cable-driven robot with translational motion

The design of a new cable-driven robot for large-scale manipulation is presented with focus on the tension condition in the cables. In this robot, the arrangement of the cables is such that the moving platform has three translational motions. The robot has potentials for large-scale robotic manipulations, machining of large parts and material handling. The design analysis presented here is towards the synthesis of the robot as well as the sizing of the actuators and cables. The synthesis of this robot is dependent on the results of the tensionable workspace analysis previously published by the Alikhani et al. [6]. The analysis of the cable forces is presented in detail, which is then used to size the actuators. For this purpose, a geometrical approach is used to represent the capability of the end-effector for applying forces and moments as convex polyhedra. The design problem is then reduced to the sizing of these polyhedra according to the design requirements and manufacturing limitations. A prototype is also designed and fabricated, which is presented at the end to further elaborate on the proposed approach.     

Singular perturbation approach to trajectory tracking of flexible robot with joint elasticity

The control problem of a robot manipulator with flexures both in the links and joints was investigated using the singular perturbation technique. Owing to the combined efects of the link and joint jlexibilities, the dynamics of this type of manipulator become more complex and under-actuated leading to a challenging control task. The singular perturbation being a successful technique for solving control problems with under-actuation was exploited to obtain simpler subsystems with two-time-scale separation, thus enabling easier design of subcontrollers. Furthermore, simultaneous tracking and suppression of vibration of the link andjoint of the manipulator is possible by application of the composite controller, i.e. the superposition of both subcontrol actions. In the first instance, the design of a composite controller was based on a computed torque control for slow dynamics and linear-quadratic fast control. Later, to obtain an improved control performance under model uncertainty, the composite control action was achieved using the radial basis function neural network for the slow control and a linear-quadratic fast control. It was confirmed through numerical simulations that the proposed singular perturbation controllers suppress the joint and link vibrations of the manipulator satisfactorily while a perfect trajectory tracking was achieved.     

一种角色运动轨迹提取及重定向的方法

随着计算机图形学和动漫产业的快速发展,通过计算机实现运动编辑和运动重定向技术,形成角色动作库进行重复利用,成为快速生产动漫作品的一个重要手段。提出了一种角色运动轨迹提取及重定向的方法。该方法通过记录角色末端关节的运动轨迹,通过一定的归一化规则提取建立角色运动轨迹库,利用CCD逆向运动学解算器重定向至另外一个角色,实现角色动作的重复利用,达到了较为理想的效果。     

Identification of a trajectory generator model for the PUMA-560 robot

In this article, work on the experimental identification of a model of the trajectory generator of a PUMA-560 robot is reported. The model developed is based on theoretical work reported in the literature and the necessary parameters are obtained experimentally. The resulting model is validated versus the corresponding actual robot motions. All experiments are based on the use of a 3D non-contact position sensor to record the motions of the robot end-effector. © 1994 John Wiley & Sons, Inc.     

Motion trajectory of human arms based on the dual quaternion with motion tracker

In this paper, we present an algorithm for human motion capture of the real-time motion trajectory of human arms based on wireless inertial 3D motion trackers. It aims to improve the accuracy of inertial motion captures and quickly reconstruct some human movements. To evaluate the performance of the proposed dual quaternion algorithm, we present the prototype design. The wireless inertial measurement system and Kinect device are introduced simultaneously in capturing human motion. The dual quaternion algorithm incorporates features of the quaternion rotation and translation. So the singular points of Euler angles can be avoided. Dual quaternion algorithm and DCM(direction cosine matrix) are used to reconstruct human arm movements respectively. Compared with the computing speed in Matlab, the speed of the dual quaternion is faster than it of DCM. To the end, we propose a 3D ADAMS human robotic model for simulating the motion trajectory using dual quaternion algorithm. The results show that the dual quaternion can achieve capabilities of a positive DCM solving, which completed between body segments rotating and translating the coordinate system transformation. Also it can effectively drive in real-time a human model to animate movement, and provide a good algorithm.     

A motion control for a spherical robot with pendulum drive

Problems of controlling a spherical robot with pendulum drive are considered. A mathematical model of the dynamics of this robot is constructed and control laws in the form of state feedback that provide robot motion along a given trajectory are synthesized. Results of computer simulation that demonstrate efficiency of the proposed control laws are presented.     

Reaching for redundant arms with human-like motion and compliance properties

This work proposes a redundant arm torque controller for reaching, guaranteeing desired completion time and accuracy requirements without the need for trajectory planning and prior knowledge of robot dynamics. The proposed controller is designed based on the prescribed performance control methodology and it is a reaching regulator in which the target pose for the hand acts as an attractor for the arm. It provides configuration consistency in return motions and hand and joint velocity smoothness. Its use in an admittance control scheme given measurements or estimates of external forces is also proposed providing active compliance capabilities in robot–environment interactions. Simulation studies for a 5dof human arm-like robot and experiments with a 7dof arm are performed to verify the approach and demonstrate the proposed controller’s performance.     

Adaptive motion control of wheeled mobile robot with unknown slippage

As a major representative nonholonomic system, wheeled mobile robot (WMR) is often used to travel across off-road environments that could be unstructured environments. Slippage often occurs when WMR moves in slopes or uneven terrain, and the slippage generates large accumulated position errors in the vehicle, compared with conventional wheeled mobile robots. An estimation of the wheel slip ratio is essential to improve the accuracy of locomotion control. In this paper, we propose an improved adaptive controller to allow WMR to track the desired trajectory under unknown longitudinal slip, where the stabilisation of the closed-loop tracking system is guaranteed by the Lyapunov theory. All system states use neural network online weight tuning algorithms, which ensure small tracking errors and no loss of stability in robot motion with bounded input signals. We demonstrate superior tracking results using the proposed control method in various Matlab simulations.