Robot Position Control Research Articles

New AFSMC Method for Nonlinear System with State-dependent Uncertainty: Application to Hexapod Robot Position Control

Conventional Adaptive Fuzzy Sliding Mode Control (AFSMC) method is extended for nonlinear affine systems with state-dependent upper bound of uncertainties. More general affine model of the system with state-dependent uncertainties is proposed where such a model is more applicable in robotics. Position control of a Stewart Manipulator (SM) is then considered as a challenging case study to experimentally verify the effectiveness of the proposed Extended AFSMC (E-AFSMC) method. The proposed method is encompassed of a fuzzy system for estimation of a nonlinear system, a robust controller for compensation of uncertainties and some appropriate adaptation laws for optimization of performance. The second Lyapunov theorem and Barbalat lemma are used to prove the closed-loop asymptotic stability. Furthermore, numerical simulations depict the robustness of the proposed controller and in particular, under the very critical situation of actuator saturation and unexpected uncertainties. The effectiveness of the proposed control method is validated through experimental results.

생체모방형 제어 알고리즘 기반의 메카넘휠 로봇 위치 제어

생체모방형 제어 알고리즘 기반의 메카넘휠 로봇 위치 제어

Intelligent robotic gripper with adaptive grasping force

The on-off control robot gripper is widely employed in pick-and-place operations in Cartesian space for handling hard objects between two positions. Without contact force monitoring, it can not be applied in fragile or soft objects handling. Although, an appropriate grasping force or gripper opening for each target could be searched by trial-and-error process, it needs expensive force/torque sensor or an accurate gripper position controller. It has too expensive and complex control strategy disadvantages for most of industrial applications. In addition, it can not overcome the target slip problem due to mass uncertainty and dynamic factor. Here, an intelligent gripper is designed with embedded distributed control structure for overcoming the uncertainty of object’s mass and soft/hard features. A communication signal is specified to integrate both robot arm and gripper control kernels for executing the robotic position control and gripper force control functions in sequence. An efficient model-free intelligent fuzzy sliding mode control strategy is employed to design the position and force controllers of gripper, respectively. Experimental results of pick-and-place soft and hard objects with grasping force auto-tuning and anti-slip control strategy are shown by pictures to verify the dynamic performance of this distributed control system. The position and force tracking errors are less than 1 mm and 0.1 N, respectively.

Image Processing for Autonomous Positioning of Eye Surgery Robot in Micro-Cannulation

Vitreoretinal surgery tasks are difficult even for expert surgeons. Therefore, an eye-surgery robot has been developed to assist surgeons in performing such difficult tasks accurately and safely. In this paper, the autonomous positioning of a micropipette mounted on an eye-surgery robot is proposed; specifically, the shadow of the micropipette is used for positioning in the depth direction. First, several microscopic images of the micropipette and its shadow are obtained, and the images are manually segmented into three regions, namely, the micropipette, its shadow, and the eye ground regions. Next, each pixel of the segmented regions is labeled, and labeled images are used as ground-truth data. Subsequently, the Gaussian Mixture Model (GMM) is used by the eye surgery robot system to learn the sets of the microscope images and their corresponding ground-truth data using the HSV color information as feature values. The GMM model is then used to estimate the regions of the micropipette and its shadow in a real-time microscope image as well as their tip positions, which are utilized for the autonomous robotic position control. After the planar positioning is performed using the visual servoing method, the micropipette is moved to approach the eye ground until the distance between the tip of the micropipette and its shadow is either equal to or less than a predefined threshold. Thus, the robot could accurately approach the eye ground and safely stop before contact. An autonomous positioning task is performed ten times in a simulated eye-surgery setup, and the robot stops at an average height of 1.37mm from a predefined target when the threshold is 1.4mm. Further enhancement in the estimation accuracy in the image processing would improve the positioning accuracy and safety.

Development and control of a unicycle robot with double flywheels

Balancing the unicycle robot is a challenging topic for control and mechanical design. The robot has to robustly balance itself in both longitudinal and lateral directions under uncertain disturbances and inherent non-linear effects. This paper presents the development and control of a unicycle robot which utilizes double-flywheel technique for roll (lateral) control and the inverted-pendulum technique for pitch (longitudinal) control. The non-linear dynamic model is derived by Lagrangian approach. The linearized model is approximated around upright position and identified. The unicycle robot prototype is designed and controlled. Linear quadratic regulator with integral action (LQR+I) is proposed to balance the robot in both directions and compared with the conventional LQR. Simulation and experimental results of balancing control and robot position control are presented. The results significantly show superior performance of LQR+I over LQR.

Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots

ABSTRACTThis paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.

Neurofuzzy self-tuning of the dissipation rate gain for model-free force-position exponential tracking of robots

Simultaneous force and position control of robots interacting with a rigid environment has been broadly studied assuming several contact force models, being the differential algebraic – DAE – model the most complete one, however DAE robots show complex and strong nonlinear couplings that make difficult to achieve tracking, when dynamic model is not available. In this paper, considering the fundamental structural properties of DAE robots, in particular passivity and the orthogonalization of force and velocity vectors, it is proposed a model-free neurofuzzy-based self-tuning robot controller for exponential tracking, which is composed of orthogonalized PID-position plus an I-force (If) control terms, and a feed-forward desired force term. The salient feature of this proposal is a novel neurofuzzy self-tuning scheme aimed at tuning the dissipation rate gain (DRG) so as to enforce dissipativity in closed-loop, rather than the standard scheme of tuning the feedback control gains, or the control structure, which in our case stands for a simple constant feedback gain orthogonalized PID+If controller. In fact, in virtue of such orthogonalization, it emerges a simple and low cost parallel structure of the neuro-fuzzy network that targets solely the DRG so as to drive error dynamics to zero with exponential rate, without any knowledge of robot dynamics or carrying out any approximation of inverse dynamics. Thus, this technique can be applied to other class of systems and controllers that ensure passivity in closed-loop. Simulations show the validity and the feasibility of this new approach.

Modeling of Leadscrew using stepper motor

Recent developments on actuator in the field of mechatronics leads to customization of various applications such as precision movement of robot arm or position control either in hardness testing machine or removing a work piece from conveyor. The design of stepper motor provides a constant holding torque without need for the motor to be powered & provided that the motor is used within its limits, positioning error don’t occur, since stepper motors have physically predefined stations. This communication provides the different dynamic performance analysis of two phase bipolar permanent magnet hybrid stepper motor under no load, rated load & overload conditions along with modelling Leadscrew. The model implemented using Matlab/Simulink tool and the results analyse operating conditions for the stepper motor. The angular & linear displacement of Leadscrew are controlled by the actuator. The performance characteristics of lead screw are good with theoretical aspects

홈 웰니스 로봇의 사물인터넷 기반 지능형 자기 위치 및 자세 제어

홈 웰니스 로봇의 사물인터넷 기반 지능형 자기 위치 및 자세 제어

SOFT FOOD ROBOTIC PICK AND PLACE OPERATION WITH EMBEDDED CONTROL STRUCTURE

Robotic pick-and-place operation is planned for handling hard objects with on-off control gripper. It does not have force monitoring capability for safe grasping soft objects. Current force/torque sensor is too expensive and difficult to implement. Here, a low cost embedded control structure is designed with distributed FPGA robotic position control and gripper Arduino force control kernels. A model-free intelligent fuzzy sliding mode control strategy is employed to design the position controller of each robotic joint and gripper force controller. Experimental results show that the position and force tracking control errors of this robotic system are less than 1 mm and 0.1 N, respectively for pick-and-place different soft foods.

3D two-fingered caging for two types of objects: sufficient conditions and planning

Caging is a method to capture an object geometrically by robots. Position-controlled robots can make the object inescapable from the robot formation. Moreover less number of mobile robots or a robot hand with low degrees of freedom can constrain the object with considering concavity of the object. In this paper, we propose two types of caging: ring-type and waist-type, which both can be accomplished by a two-fingered hand. We derive sufficient conditions for caging of the two types and construct RRT-based motion planner for caging by a robotic arm/hand system. In motion planning, we find one of final configurations that satisfy the sufficient conditions and produce a path of robot configuration to the goal. With object recognition using AR picture markers, we can acquire geometrical information of objects and plan robot motion for caging. We show some experimental results of planning and execution of planned caging motion for four objects.

Biped Robot Position Control with Stability-Based Ground Reaction Force and Velocity Constraints

Biped Robot Position Control with Stability-Based Ground Reaction Force and Velocity Constraints

Nonlinear Bifurcation Analysis of a Single-DoF Model of a Robotic Arm Subject to Digital Position Control

Abstract Precision and stability in position control of robots are critical parameters in many industrial applications where high accuracy is needed. It is well known that digital effect is destabilizing and can cause instabilities. In this paper, we analyze a single DoF model of a robotic arm and we present the stability limits in the parameter space of the control gains. Furthermore we introduce a nonlinearity relative to the saturation of the control force in the model, reduce the dynamics of the nonlinear map to its local center manifold, study the bifurcation along the stability border and identify conditions under which a supercritical or subcritical bifurcation occurs. The obtained results explain some of the typical instabilities occurring in industrial applications. We verify the obtained results through numerical simulations.

1A1-K01 二次元空間におけるIn-handケージングマニピュレーション(ロボットハンドの機構と把持戦略(1))

In this paper, we proposed a new method called "in-hand caging manipulation" to manipulate objects in position-controlled robot hands. In this method, the objects are caged by the hands throughout manipulation and localized around the goal as a result of the deformation of the cage. Manipulation of a circular object was successfully performed by a two-fingered robot hand in experiments. However, manipulation failed in some cases due to jamming. This problem can be solved partially by reducing friction, but further investigation is necessary.

Position Control of Flexible Joint Robots by Adapting Methods for Rigid Robots

AbstractIn this paper, it is demonstrated that many position control laws developed for rigid joint robots can also be used for flexible joint robots after some modifications. The main assumptions are smoothness of the control law and the availability of a Lyapunov function. The adaptation is based on a simple control principle: With the help of a position control method known from rigid joint robots, desired values for the motor positions are determined. If the motor positions and their desired values are identical, the link positions converge to their desired trajectories. Afterwards, the system inputs are specified such that the motor positions converge to their desired values. The method can also be applied under system uncertainties.

Evolutionary Design of Fuzzy Logic Based Position Controller for Mobile Robot

This paper develops a fuzzy logic based position controller whose membership functions are tuned by genetic algorithm. The main goal is to ensure successful velocity and position trajectories tracking between the mobile robot and the virtual reference cart. The proposed fuzzy controller has two inputs and two outputs. The first input represents the distance between the mobile robot and the reference cart. The second input is the angle formed by the straight line defined with the orientation of the robot, and the straight line that connects the robot with the reference cart. The outputs represent linear and angular velocity commands, respectively. The performance of the fuzzy controller is validated through comparison with previously developed mobile robot position controller based on control Lyapunov functions (CLF). Simulation results indicate good performance of position tracking while at the same time a substantial reduction of the control torques is achieved.

Hardware-Software Co-Design Tracking System for Predictable High-Speed Mobile Microrobot Position Control

Fast closed-loop control is a key issue for high-throughput automated micro-and nanohandling. Currently, mobile robot position control relies on computer vision using FireWire- or USB-cameras. This approach has several drawbacks for closed-loop control, such as limited update rate, high latency and unpredictable jitter. To overcome these drawbacks, a new hardware-based position tracking algorithm is presented and compared to current position control sensors. Additionally, several measurements of a closed-loop controlled mobile robot for micro- and nanohandling show the system's advanced performance in terms of speed and accuracy using the new sensor.

三次元多指ケージングの十分条件の導出―対称ハンドによる四種類の単純形状物体の拘束―

Caging is a geometrical method to constrain an object: a position-controlled robot surrounds the object to make it be inescapable from the cage composed by the robot bodies. In this paper, we propose three-dimensional caging by a multifingered hand (3D multifingered caging). In multifingered caging, force control is not necessary to constrain an object. This is an advantage over conventional grasping from the viewpoint of easy execution by actual robots. Furthermore, considering a margin of caging constraint allows the error of position control and deformation of objects to some extent. We classify 3D multifingered caging according to states of constraint, and derive sufficient conditions for caging of some simple-shaped objects. We show some configurations of a robot hand for caging planned with the sufficient conditions.

Cooperative robotic assistant with drill‐by‐wire end‐effector for spinal fusion surgery

PurposeThe purpose of this paper is to present a surgical robot for spinal fusion and its control framework that provides higher operation accuracy, greater flexibility of robot position control, and improved ergonomics.Design/methodology/approachA human‐guided robot for the spinal fusion surgery has been developed with a dexterous end‐effector that is capable of high‐speed drilling for cortical layer gimleting and tele‐operated insertion of screws into the vertebrae. The end‐effector is position‐controlled by a five degrees‐of‐freedom robot body that has a kinematically closed structure to withstand strong reaction force occurring in the surgery. The robot also allows the surgeon to control cooperatively the position and orientation of the end‐effector in order to provide maximum flexibility in exploiting his or her expertise. Also incorporated for improved safety is a “drill‐by‐wire” mechanism wherein a screw is tele‐drilled by the surgeon in a mechanically decoupled master/slave system. Finally, a torque‐rendering algorithm that adds synthetic open‐loop high‐frequency components on feedback torque increases the realism of tele‐drilling in the screw‐by‐wire mechanism.FindingsExperimental results indicated that this assistive robot for spinal fusion performs drilling tasks within the static regulation errors less than 0.1 μm for position control and less than 0.05° for orientation control. The users of the tele‐drilling reported subjectively that they experienced torque feedback similar to that of direct screw insertion.Research limitations/implicationsAlthough the robotic surgery system itself has been developed, integration with surgery planning and tracking systems is ongoing. Thus, the screw insertion accuracy of a whole surgery system with the assistive robot is to be investigated in the near future.Originality/valueThe paper arguably pioneers the dexterous end‐effector appropriately designed for spinal fusion, the cooperative robot position‐control algorithm, the screw‐by‐wire mechanism for indirect screw insertion, and the torque‐rendering algorithm for more realistic torque feedback. In particular, the system has the potential of circumventing the screw‐loosening problem, a common defect in the conventional surgeon‐operated or robot‐assisted spinal fusion surgery.

A Guideline for Low-Force Robotic Guidance for Enhancing Human Performance of Positioning and Trajectory Tracking: It Should Be Stiff and Appropriately Slow

This paper considers the application of a low-force robotic manipulator to guide a human user's movements to place a tool (or the user's hand) at a predetermined position or move it along a predetermined trajectory. This application is potentially useful, e.g., skill training for humans, rehabilitation, and human-machine coordination in the manufacturing industry. A proportional-derivative (PD)-type position control can be used for this application, but the parameters for the controller should be appropriately chosen for enhancing the human performance of positioning and trajectory tracking. We hypothesize that the robot's position control should be stiff and appropriately slow, i.e., the proportional gain should be high and the time constant (the ratio of the derivative gain to the proportional gain) should be appropriately large. Such characteristic has been difficult to be realized in ordinary PD position control because it requires direct high-gain velocity feedback. However, our recent technique, which is proxy-based sliding mode control (PSMC), is capable of producing such a hypothetically preferred response and allows us to empirically validate the hypothesis. The results of experiments using two distinctly different robotic devices supported the hypothesis, showing that the time constant should be set around 0.1 s rather than 0.01 and 0.5 s.