Development of a 3-DOF Tripedal Stick-Slip Microrobotic Mobile Platform for Unconstrained, Omnidirectional Sample Positioning

2018 ◽  
Author(s):  
Iman Adibnazari ◽  
William S. Nagel ◽  
Kam K. Leang
Keyword(s):  
Visual Servoing ◽  
Feedforward Control ◽  
Low Cost ◽  
Tracking Error ◽  
Kinematic Model ◽  
Open Loop ◽  
Step Cycle ◽  
Stick Slip ◽  
Slip Step ◽  
Forward Kinematic

This paper presents the development of a piezo-based three-degree-of-freedom (3-DOF), tripedal microrobotic platform that allows for unlimited travel with sub-micron precision over a planar surface. Compliant mechanical amplifiers are incorporated with each piezoelectric stack actuator to improve both the stroke and load-bearing capability of the platform. A forward kinematic model of the stage based on its tripedal leg architecture is derived for each stick-slip step cycle and inverted for feedforward control of the platform. A prototype is constructed using low-cost 3D-printing techniques. Experimental results demonstrate actuator stroke of 29.4 μm on average with a dominant resonance of approximately 860 Hz. Results demonstrate the stage tracks a 3 mm by 3 mm square trajectory in open loop. Feedback control through visual servoing is then simulated on a model that includes flexure dynamics, observed surface interactions, and camera sampling times, reducing the root-mean-square (RMS) tracking error by 90%. This control scheme is then implemented experimentally, resulting in 99% RMS position error reduction relative to when only feedforward control is used.

scholarly journals Kinematic Model and Real-Time Path Generator for a Wire-Driven Surgical Robot Arm with Articulated Joint Structure

2019 ◽  
Vol 9 (19) ◽  
pp. 4114 ◽  
Author(s):  
Jin ◽  
Lee ◽  
Lee ◽  
Han
Keyword(s):  
Kinematic Model ◽  
Joint Space ◽  
Open Loop ◽  
Surgical Robot ◽  
Path Generation ◽  
Robot Arm ◽  
Open Loop Control ◽  
Loop Control ◽  
Joint Structure ◽  
Forward Kinematic

This paper presents a forward kinematic model of a wire-driven surgical robot arm with an articulated joint structure and path generation algorithms with solutions of inverse kinematics. The proposed methods were applied to a wire-driven surgical robot for single-port surgery. This robot has a snake-like robotic arm with double segments to fit the working space in a single port and a joint structure to secure stiffness. The accuracy of the model is highly important because small surgical robot arms are usually controlled by open-loop control. A curvature model is widely used to describe and control a continuum robotic body. However, the model is quite different from a continuum robotic arm with a joint structure and can lead to slack of the driving wires or decreased stiffness of the joints. An accurate forward kinematic model was derived to fit the actual hardware structure via the frame transformation method. An inverse kinematic model from the joint space to the wire-length space was determined from an asymmetric model for the joint structure as opposed to a symmetric curvature model. The path generation algorithm has to generate a command to send to each actuator in open-loop control. Two real-time path generation algorithms that solve for inverse kinematics from the task space to the joint space were designed and compared using simulations and experiments. One of the algorithms is an optimization method with sequential quadratic programming (SQP), and the other uses differential kinematics with a PID (Proportional-Integral-Derivative) control algorithm. The strengths and weaknesses of each algorithm are discussed.

Dynamics of a Stepping Motor Driven Conventional Machine Slide

1988 ◽  
Author(s):  
E. I. Umez-Eronini
Keyword(s):  
Low Cost ◽  
Open Loop ◽  
Motor Drives ◽  
Numerical Control ◽  
Stepping Motor ◽  
Stick Slip ◽  
Loop Control ◽  
Drive Chain ◽  
Conventional Machine ◽  
Drive Systems

Abstract A model of a conventional, manually driven machine tool slide which is retrofitted for Numerical Control by merely incorporating high-power stepping motor drives, is developed. This model includes the relatively large amount of stick-slip friction in the slideways, and backlash in the drive chain, which characterize the conventional slide. Simulation results obtained using this model highlight the peculiar dynamic behavior, at low speed positioning and contouring operations, of such large stepping motor drive systems under electronically damped open-loop control. The results also demonstrate the feasibility of this low-cost approach to the retrofitting problem, given adequate open- or closed-loop controllers, and provide useful insight into the design of such control systems.

Predictive Friction Compensation for Control of Pneumatic Actuators

2014 ◽  
Author(s):  
Hannes G. Daepp ◽  
Wayne J. Book
Keyword(s):  
Low Cost ◽  
Tracking Error ◽  
Force Density ◽  
Friction Compensation ◽  
Time Step ◽  
Third Order ◽  
Stick Slip ◽  
Pneumatic Actuators ◽  
Prediction Horizon ◽  
Predictive Controller

Pneumatic actuators possess several attractive qualities: high power and force density, potentially adaptable compliance, and clean, safe, and low cost actuation. However, control of pneumatic actuators has proven difficult, limited by inherent compliance of the actuator, nonlinear and discontinuous third order dynamics, and friction. Stiction and compliance lead to a sandwiched nonlinearity that causes stick-slip and can cause significant tracking error and even instability. A broadly applicable method of friction compensation is addition of a feedforward term updated from a friction estimate at each time step. Since pneumatic dynamics are slow, achievable compensation can be insufficient. In this work, friction is estimated over a prediction horizon and then input into a model-based predictive controller as an offset term, so that compensation is planned and optimal over the prediction horizon. The controller is tested in simulation. Results are compared to control using instantaneous compensation and are characterized based on performance.

Open Loop Speed Control Of Brushless DC Motor Using Low Cost Arduino UNO Processor

2016 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Potnuru Devendra ◽  
Mary K. Alice ◽  
Ch. Sai Babu ◽  
◽  
◽  
...  
Keyword(s):  
Low Cost ◽  
Speed Control ◽  
Dc Motor ◽  
Open Loop ◽  
Brushless Dc Motor ◽  
Brushless Dc ◽  
Arduino Uno

SateLoc: A Virtual Fingerprinting Approach to Outdoor LoRa Localization Using Satellite Images

2021 ◽  
Vol 17 (4) ◽  
pp. 1-28
Author(s):  
Yuxiang Lin ◽  
Wei Dong ◽  
Yi Gao ◽  
Tao Gu
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Satellite Images ◽  
Low Cost ◽  
Tracking Error ◽  
Location Based Services ◽  
Distance Constraint ◽  
Combination Strategy ◽  
Land Cover Types ◽  
High Resolution Satellite Images

With the increasing relevance of the Internet of Things and large-scale location-based services, LoRa localization has been attractive due to its low-cost, low-power, and long-range properties. However, existing localization approaches based on received signal strength indicators are either easily affected by signal fading of different land-cover types or labor intensive. In this work, we propose SateLoc, a LoRa localization system that utilizes satellite images to generate virtual fingerprints. Specifically, SateLoc first uses high-resolution satellite images to identify land-cover types. With the path loss parameters of each land-cover type, SateLoc can automatically generate a virtual fingerprinting map for each gateway. We then propose a novel multi-gateway combination strategy, which is weighted by the environmental interference of each gateway, to produce a joint likelihood distribution for localization and tracking. We implement SateLoc with commercial LoRa devices without any hardware modification, and evaluate its performance in a 227,500-m urban area. Experimental results show that SateLoc achieves a median localization error of 43.5 m, improving more than 50% compared to state-of-the-art model-based approaches. Moreover, SateLoc can achieve a median tracking error of 37.9 m with the distance constraint of adjacent estimated locations. More importantly, compared to fingerprinting-based approaches, SateLoc does not require the labor-intensive fingerprint acquisition process.

Iterative learning control algorithm for sensor fault nonlinear systems

2020 ◽  
pp. 1-8
Author(s):  
Zimian Lan
Keyword(s):  
Nonlinear Systems ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Tracking Error ◽  
Learning Control ◽  
Open Loop ◽  
Iterative Learning ◽  
Sensor Fault ◽  
Initial State ◽  
Control Gain

In this paper, we propose a new iterative learning control algorithm for sensor faults in nonlinear systems. The algorithm does not depend on the initial value of the system and is combined with the open-loop D-type iterative learning law. We design a period that shortens as the number of iterations increases. During this period, the controller corrects the state deviation, so that the system tracking error converges to the boundary unrelated to the initial state error, which is determined only by the system’s uncertainty and interference. Furthermore, based on the λ norm theory, the appropriate control gain is selected to suppress the tracking error caused by the sensor fault, and the uniform convergence of the control algorithm and the boundedness of the error are proved. The simulation results of the speed control of the injection molding machine system verify the effectiveness of the algorithm.

scholarly journals Integration of GPS, Monocular Vision, and High Definition (HD) Map for Accurate Vehicle Localization

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3270 ◽  
Author(s):  
Hao Cai ◽  
Zhaozheng Hu ◽  
Gang Huang ◽  
Dunyao Zhu ◽  
Xiaocong Su
Keyword(s):  
Kalman Filter ◽  
Low Cost ◽  
Kinematic Model ◽  
Intelligent Vehicles ◽  
Monocular Vision ◽  
Measurement Unit ◽  
High Definition ◽  
Position Information ◽  
Vehicle Localization ◽  
Lateral Distance

Self-localization is a crucial task for intelligent vehicles. Existing localization methods usually require high-cost IMU (Inertial Measurement Unit) or expensive LiDAR sensors (e.g., Velodyne HDL-64E). In this paper, we propose a low-cost yet accurate localization solution by using a custom-level GPS receiver and a low-cost camera with the support of HD map. Unlike existing HD map-based methods, which usually requires unique landmarks within the sensed range, the proposed method utilizes common lane lines for vehicle localization by using Kalman filter to fuse the GPS, monocular vision, and HD map for more accurate vehicle localization. In the Kalman filter framework, the observations consist of two parts. One is the raw GPS coordinate. The other is the lateral distance between the vehicle and the lane, which is computed from the monocular camera. The HD map plays the role of providing reference position information and correlating the local lateral distance from the vision and the GPS coordinates so as to formulate a linear Kalman filter. In the prediction step, we propose using a data-driven motion model rather than a Kinematic model, which is more adaptive and flexible. The proposed method has been tested with both simulation data and real data collected in the field. The results demonstrate that the localization errors from the proposed method are less than half or even one-third of the original GPS positioning errors by using low cost sensors with HD map support. Experimental results also demonstrate that the integration of the proposed method into existing ones can greatly enhance the localization results.

scholarly journals Kinematics modeling and simulation of an autonomous omni-directional mobile robot

2015 ◽  
Vol 35 (2) ◽  
pp. 74-79 ◽  
Author(s):  
Daniel Garcia Sillas ◽  
Efrén Gorrostieta Hurtado ◽  
Emilio Vargas Soto ◽  
Juvenal Rodríguez Reséndiz ◽  
Saúl Tovar Arriaga
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Kinematic Model ◽  
Model Development ◽  
Physical Behavior ◽  
Kinematics Modeling ◽  
Wheeled Robot ◽  
Potential Problems ◽  
Test Behavior ◽  
Virtual Platform

<p class="Abstractandkeywordscontent"><span lang="EN-US">Although robotics has progressed to the extent that it has become relatively accessible with low-cost projects, there is still a need to create models that accurately represent the physical behavior of a robot. Creating a completely virtual platform allows us to test behavior algorithms such as those implemented using artificial intelligence, and additionally, it enables us to find potential problems in the physical design of the robot. The present work describes a methodology for the construction of a kinematic model and a simulation of the autonomous robot, specifically of an omni-directional wheeled robot. This paper presents the kinematic model development and its implementation using several tools. The result is a model that follows the kinematics of a triangular omni-directional mobile wheeled robot, which is then tested by using a 3D model imported from 3D Studio</span><span lang="EN-US">®</span><span lang="EN-US"> and Matlab</span><span lang="EN-US">® for the simulation. The environment used for the experiment is very close to the real environment and reflects the kinematic characteristics of the robot.</span></p>

DUTY-CYCLED SPINNING BASED 3D MOTION CONTROL APPROACH FOR BEVEL-TIPPED FLEXIBLE NEEDLE INSERTION

2018 ◽  
Vol 18 (07) ◽  
pp. 1840017 ◽  
Author(s):  
QIN YAO ◽  
XUMING ZHANG
Keyword(s):  
Motion Control ◽  
Control Method ◽  
Tracking Error ◽  
Open Loop ◽  
Loop Control ◽  
3D Motion ◽  
Control Approach ◽  
Target Error ◽  
The Mean ◽  
Simulation Results

Flexible needle has been widely used in the therapy delivery because it can advance along the curved lines to avoid the obstacles like important organs and bones. However, most control algorithms for the flexible needle are still limited to address its motion along a set of arcs in the two-dimensional (2D) plane. To resolve this problem, this paper has proposed an improved duty-cycled spinning based three-dimensional (3D) motion control approach to ensure that the beveled-tip flexible needle can track a desired trajectory to reach the target within the tissue. Compared with the existing open-loop duty-cycled spinning method which is limited to tracking 2D trajectory comprised of few arcs, the proposed closed-loop control method can be used for tracking any 3D trajectory comprised of numerous arcs. Distinctively, the proposed method is independent of the tissue parameters and robust to such disturbances as tissue deformation. In the trajectory tracking simulation, the designed controller is tested on the helical trajectory, the trajectory generated by rapidly-exploring random tree (RRT) algorithm and the helical trajectory. The simulation results show that the mean tracking error and the target error are less than 0.02[Formula: see text]mm for the former two kinds of trajectories. In the case of tracking the helical trajectory, the mean tracking error target error is less than 0.5[Formula: see text]mm and 1.5[Formula: see text]mm, respectively. The simulation results prove the effectiveness of the proposed method.

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