scholarly journals DESIGN & KINEMATIC ANALYSIS OF AN ARTICULATED ROBOTIC MANIPULATOR

2014 ◽  
pp. 12-15
Author(s):  
ELIAS ELIOT ◽  
B.B.V.L. DEEPAK ◽  
D.R. PARHI ◽  
J. SRINIVAS
Keyword(s):  
Kinematic Model ◽  
Robotic Manipulator ◽  
Path Tracking ◽  
Primary Level ◽  
Industrial Manipulator ◽  
Pick And Place ◽  
Position And Orientation ◽  
End Effectors ◽  
Forward Kinematic ◽  
Five Axes

This paper describes the design, fabrication and analysis a five axes articulated robotic manipulator. The current work is undertaken by considering various commercially available robotic kits to design and fabricate a five degree of freedom (D.O.F) arm. Forward kinematic model has been presented in order to determine the end effectors position and orientation. Although this work is still in primary level, this analysis is useful for path tracking of an industrial manipulator with pick-and-place application. Based on this analysis, a researcher can develop path tracking behaviour of an end effector in complicated work space.

An Algorithm for Generation of Coordinated Robot Trajectories in Cartesian Space

2013 ◽  
Vol 196 ◽  
pp. 169-180 ◽  
Author(s):  
Adam Słota
Keyword(s):  
Virtual Environment ◽  
Relative Position ◽  
Accuracy Analysis ◽  
Simulation Environment ◽  
Coordinated Motion ◽  
Generation Algorithm ◽  
Cartesian Space ◽  
Position And Orientation ◽  
End Effectors ◽  
Trajectory Generation Algorithm

In the paper a trajectory generation algorithm for two robots’ coordinated motion is presented. Two instances of the algorithm, each for one robot, run in the same time and calculate trajectories’ position and orientation coordinates. Initial and end robots’ end-effectors poses are defined and values of linear and angular speeds are programmed. To minimize relative position and orientation errors an idea of corrective motion is introduced. Trajectory coordinates are calculated as the sum of programmed and corrective motion. The algorithm was implemented in a simulation environment and results of simulation are presented. Static accuracy analysis for general case and stability verification for fixed values of robots’ parameters are described. Finally, an outline of proposed procedure of building a virtual environment for reachability verification and collision checking is presented.

A Model of the Human Spine: Forward and Inverse Kinematics

1992 ◽  
Author(s):  
Sunil Kumar Agrawal ◽  
Siyan Li ◽  
Glen Desmier
Keyword(s):  
Range Of Motion ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Joint Angles ◽  
Human Spine ◽  
Forward And Inverse Kinematics ◽  
Position And Orientation ◽  
Three Degrees Of Freedom ◽  
Adjacent Vertebra

Abstract The human spine is a sophisticated mechanism consisting of 24 vertebrae which are arranged in a series-chain between the pelvis and the skull. By careful articulation of these vertebrae, a human being achieves fine motion of the skull. The spine can be modeled as a series-chain with 24 rigid links, the vertebrae, where each vertebra has three degrees-of-freedom relative to an adjacent vertebra. From the studies in the literature, the vertebral geometry and the range of motion between adjacent vertebrae are well-known. The objectives of this paper are to present a kinematic model of the spine using the available data in the literature and an algorithm to compute the inter vertebral joint angles given the position and orientation of the skull. This algorithm is based on the observation that the backbone can be described analytically by a space curve which is used to find the joint solutions..

Development of Path Tracking Control Algorithm for a 4 DOF Spatial Manipulator Using PID Controller

2017 ◽  
pp. 314-327
Author(s):  
Pradeep Reddy Bonikila ◽  
Ravi Kumar Mandava ◽  
Pandu Ranga Vundavilli
Keyword(s):  
Pid Controller ◽  
Dynamic Models ◽  
Control Method ◽  
Robotic Manipulator ◽  
Industrial Applications ◽  
Path Tracking ◽  
End Effector ◽  
Straight Line ◽  
Feedback Control Method ◽  
Manipulator Arm

The path tracking phenomenon of a robotic manipulator arm plays an important role, when the manipulators are used in continuous path industrial applications, such as welding, machining and painting etc. Nowadays, robotic manipulators are extensively used in performing the said tasks in industry. Therefore, it is essential for the manipulator end effector to track the path designed to perform the task in an effective way. In this chapter, an attempt is made to develop a feedback control method for a 4-DOF spatial manipulator to track a path with the help of a PID controller. In order to design the said controller, the kinematic and dynamic models of the robotic manipulator are derived. Further, the concept of inverse kinematics has been used to track different paths, namely a straight line and parabolic paths continuously. The effectiveness of the developed algorithm is tested on a four degree of freedom manipulator arm in simulations.

Plant-Limited Co-Design of an Energy-Efficient Counterbalanced Robotic Manipulator

2012 ◽  
Author(s):  
James T. Allison
Keyword(s):  
System Design ◽  
Physical System ◽  
Control Design ◽  
Robotic Manipulator ◽  
Plant Design ◽  
Design Modification ◽  
Baseline Design ◽  
Design Changes ◽  
Pick And Place ◽  
Place Task

Modifying the design of an existing system to meet the needs of a new task is a common activity in mechatronic system development. Often engineers seek to meet requirements for the new task via control design changes alone, but in many cases new requirements are impossible to meet using control design only; physical system design modifications must be considered. Plant-Limited Co-Design (PLCD) is a design methodology for meeting new requirements at minimum cost through limited physical system (plant) design changes in concert with control system redesign. The most influential plant changes are identified to narrow the set of candidate plant changes. PLCD provides quantitative evidence to support strategic plant design modification decisions, including tradeoff analyses of redesign cost and requirement violation. In this article the design of a counterbalanced robotic manipulator is used to illustrate successful PLCD application. A baseline system design is obtained that exploits synergy between manipulator passive dynamics and control to minimize energy consumption for a specific pick-and-place task. The baseline design cannot meet requirements for a second pick-and-place task through control design changes alone. A limited set of plant design changes is identified using sensitivity analysis, and the PLCD result meets the new requirements at a cost significantly less than complete system redesign.

Asymmetric Arm Design on Delta Robot System

2014 ◽  
Author(s):  
Tsung-Liang Wu ◽  
Jih-Hsiang Yeh ◽  
Cheng-Chen Yang
Keyword(s):  
Energy Saving ◽  
High Speed ◽  
Kinematic Model ◽  
Industrial Applications ◽  
Critical Parameters ◽  
Robot System ◽  
System Cost ◽  
Excited Vibration ◽  
Pick And Place ◽  
Delta Robot

The Delta robot system is widely used in high speed (4 cycles/s at 25-200-25 mm) pick-and-place process in production line. Some industrial applications include photo-voltaic (PV), food process, and electronic assembly, and so on. The energy saving and system cost are two critical parameters for designing the next generation of pick-and-place system. To achieve these goals, a light-weight moving structure with sufficient strength to overcome the excited vibration will be one of the solutions. In this paper, an asymmetric arm design is proposed and fabricated to gain the benefit of strength-to-weight. The asymmetric arm is designed by reinforcing a specific direction and is validated the vibration suppression capability both by simulation and experiment. A position controller that is derived from the kinematic model of Delta robot is utilized to manipulate the robot under a forward-backward motion with a polynomial trajectory with 200 mm displacement. The residual vibration, then, was measured after the forward-backward motion to compare the settling performance between symmetric- and asymmetric-arms on the Delta robot system, respectively. The results conclude as following: (1) The asymmetric arms perform slightly worse (0.03 sec more in settling time) than symmetric arm but there is 15% weight reducing comparing to symmetric arm. (2) Both energy saving and system cost reducing would be achieved by utilizing actuators with lower power consumption and fabrication on carbon fiber arms with mass customization.

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.

Experimental Autonomous Deep Learning-Based 3D Path Planning for a 7-DOF Robot Manipulator

2019 ◽  
Author(s):  
Alex Bertino ◽  
Mostafa Bagheri ◽  
Miroslav Krstić ◽  
Peiman Naseradinmousavi
Keyword(s):  
Deep Learning ◽  
Stereo Vision ◽  
Robot Manipulator ◽  
Control Techniques ◽  
Minimal Error ◽  
Autonomous Operation ◽  
Pick And Place ◽  
Place Task ◽  
Position And Orientation ◽  
And Control

Abstract In this paper, we examine the autonomous operation of a high-DOF robot manipulator. We investigate a pick-and-place task where the position and orientation of an object, an obstacle, and a target pad are initially unknown and need to be autonomously determined. In order to complete this task, we employ a combination of computer vision, deep learning, and control techniques. First, we locate the center of each item in two captured images utilizing HSV-based scanning. Second, we utilize stereo vision techniques to determine the 3D position of each item. Third, we implement a Convolutional Neural Network in order to determine the orientation of the object. Finally, we use the calculated 3D positions of each item to establish an obstacle avoidance trajectory lifting the object over the obstacle and onto the target pad. Through the results of our research, we demonstrate that our combination of techniques has minimal error, is capable of running in real-time, and is able to reliably perform the task. Thus, we demonstrate that through the combination of specialized autonomous techniques, generalization to a complex autonomous task is possible.

scholarly journals A Survey of Single and Multi-UAV Aerial Manipulation

2020 ◽  
Vol 08 (02) ◽  
pp. 119-147 ◽  
Author(s):  
Abdullah Mohiuddin ◽  
Taha Tarek ◽  
Yahya Zweiri ◽  
Dongming Gan
Keyword(s):  
Visual Servoing ◽  
Review Paper ◽  
Environment Interaction ◽  
Aerial Manipulation ◽  
Aerial Manipulator ◽  
Pick And Place ◽  
Aerial Platforms ◽  
End Effectors ◽  
Manipulation Capability ◽  
Multi Uav

Aerial manipulation has direct application prospects in environment, construction, forestry, agriculture, search, and rescue. It can be used to pick and place objects and hence can be used for transportation of goods. Aerial manipulation can be used to perform operations in environments inaccessible or unsafe for human workers. This paper is a survey of recent research in aerial manipulation. The aerial manipulation research has diverse aspects, which include the designing of aerial manipulation platforms, manipulators, grippers, the control of aerial platform and manipulators, the interaction of aerial manipulator with the environment, through forces and torque. In particular, the review paper presents the survey of the airborne platforms that can be used for aerial manipulation including the new aerial platforms with aerial manipulation capability. We also classified the aerial grippers and aerial manipulators based on their designs and characteristics. The recent contributions regarding the control of the aerial manipulator platform is also discussed. The environment interaction of aerial manipulators is also surveyed which includes, different strategies used for end-effectors interaction with the environment, application of force, application of torque and visual servoing. A recent and growing interest of researchers about the multi-UAV collaborative aerial manipulation was also noticed and hence different strategies for collaborative aerial manipulation are also surveyed, discussed and critically analyzed. Some key challenges regarding outdoor aerial manipulation and energy constraints in aerial manipulation are also discussed.

Learning from Approximate Human Decisions by a Robot

2007 ◽  
Vol 19 (1) ◽  
pp. 68-76 ◽  
Author(s):  
Chandimal Jayawardena ◽  
◽  
Keigo Watanabe ◽  
Kiyotaka Izumi
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Natural Language ◽  
Knowledge Base ◽  
Probabilistic Neural Network ◽  
Robotic Manipulator ◽  
Human Aspects ◽  
Pick And Place ◽  
Robot Systems ◽  
Related Aspect

Robot systems operating under natural-language commands must be able to infer the meaning intended by the issuer. Despite some successful research, however, an important related aspect not yet addressed has been the possibility of learning from natural-language commands. Such commands, generated by human users, contain valuable information. The inherent subjectivity of natural language, however, complicates potential learning from such commands and their interpretation. We propose decision making for robots operating under natural-language commands influenced by human aspects of decision making. Under our proposed concept, demonstrated in experiments conducted using a robotic manipulator, the robot is controlled using natural-language commands to conduct pick-and-place operations, during which the robot builds a knowledge base. After this learning, which uses a probabilistic neural network, the robot conducts similar tasks based on approximate decisions from the knowledge gained.

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