Mapping human to robot motion with functional anthropomorphism for teleoperation and telemanipulation with robot arm hand systems

2013 ◽  
Author(s):  
Minas V. Liarokapis ◽  
Panagiotis K. Artemiadis ◽  
Kostas J. Kyriakopoulos
Keyword(s):  
Robot Motion ◽  
Robot Arm

scholarly journals Cartesian space robot manipulator clamping movement in ROS simulation and experiment

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Longtao Mu ◽  
Yunfei Zhou ◽  
Tiebiao Zhao
Keyword(s):  
Motion Planning ◽  
Position Control ◽  
Robot Manipulator ◽  
Robotic Arm ◽  
Robot Motion ◽  
Robot Arm ◽  
Operation System ◽  
Model File ◽  
Simulation And Experiment ◽  
Tool Centre Point

Abstract This paper studies the robot arm sorting position control based on robot operation system (ROS), which works depending on the characteristics of the robot arm sorting operation using the top method, to automate the sorting operation and improve the work efficiency of workpiece sorting. Through the ROS MoveIt! module, the sorting pose and movement path of the robotic arm are planned, the inverse kinematics of the sorting robotic arm is solved, and the movement pose characteristics of the sorting robotic arm are analysed. The robot arm model was created using Solidworks software, and the URDF model file of the robot arm was exported through the sw2urdf plugin conversion tool, and the parameters were configured. Based on ROS for 6-degree-of-freedom (DOF) robot motion simulation, random extended tree (RRT) algorithm from open motion planning library (OMPL) is selected. The robot motion planning analysis and sorting manipulator drive UR5 manipulator. The results show that the sorting pose and motion trajectory of the robot arm are determined by controlling the sorting pose of the sorting robot arm, and the maximum radius value of the tool centre point (TCP) rotation of the robot arm and the position of the workpiece are obtained. This method can improve the success rate of industrial sorting robots in grabbing objects. This analysis is of great significance to the research of robots’ autonomous object grabbing.

Computer simulation of sensor-based robot collision avoidance in an unknown environment

Robotica ◽  
1987 ◽  
Vol 5 (4) ◽  
pp. 291-302 ◽  
Author(s):  
K. Sun ◽  
V. Lumelsky
Keyword(s):  
Computer Simulation ◽  
Motion Planning ◽  
Collision Avoidance ◽  
Autonomous Vehicle ◽  
Planning System ◽  
Robot Motion ◽  
Robot Arm ◽  
Fixed Base ◽  
The One ◽  
Robot Path

SUMMARYComputer simulation is a major tool in validation of robot motion planning systems, since, on the one hand, underlying theory of algorithms typically requires questionable assumptions and simplifications, and, on the other hand, experiments with hardware are necessarily limited by available resources and time. This is especially true when the motion planning system in question is based on sensor feedback and the generated trajectory is, therefore, unpredictable. This paper describes a simulation system ROPAS (for RObot PAth Simulation) for testing one approach — called Dynmic Path Planning (DPP) — to sensor-based robot collision avoidance in an environment with unknown obstacles. Using real time graphics animation of the motion planning system, the user can simulate the behavior of an autonomous vehicle or a robot arm manipulator with a fixed base. The overall structure of the system is described, and examples are presented.

scholarly journals Design and Fabrication of 3-DOF Robot Arm Using Parallelogram Mechanisms

2021 ◽  
Vol 9 (9) ◽  
pp. 1224-1229
Keyword(s):  
Robotic Arm ◽  
Robot Motion ◽  
3D Printer ◽  
File Format ◽  
Robot Arm ◽  
End Effector ◽  
Stl File ◽  
Stepper Motors ◽  
And Control

This paper focuses on the design, fabrication and control of a 3-DOF robot arm using stepper motors. The robot arm uses three parallelogram mechanisms to position the end-effector of the robot and keep the end-effector always parallel to the horizontal during the robot motion. The robot is designed on the Autodesk Inventor software. Separated parts of the robot are saved in the stereolithography (STL) file format. Then the parts are fabricated by a 3D printer. The movement of the robotic arm is driven by stepper motors and controlled by Arduino. The Arduino board implements kinematics calculation, creates pulses and sends them to three drivers to driven stepper motors. A software is developed to control the robot by sending the command to the Arduino board.

A Robot Safety Experiment Varying Robot Speed and Contrast with Human Decision Cost

1988 ◽  
Vol 32 (15) ◽  
pp. 953-953 ◽  
Author(s):  
John Etherton ◽  
John E. Sneckenberger
Keyword(s):  
Experimental Situation ◽  
Industrial Robot ◽  
Robot Motion ◽  
Robot Arm ◽  
Sufficient Time ◽  
Slow Speed ◽  
Robot Safety ◽  
Human Decision ◽  
Emergency Stop ◽  
Age Range

An industrial robot safety experiment was performed to find out how quickly subjects could respond to unexpected robot motion at selected slow robot speeds and how frequently they did not respond when a signal (an unexpected motion) should have been detected. The dependent variable in the experiment was the overrun distance beyond an expected stopping point that a robot arm traveled before a person actuated a pushbutton to stop the robot. A robotics technician risks being fatally crushed if a robot should trap the person against a fixed object. This risk can be reduced if, during programming and troubleshooting tasks, the robot is moving at a slow speed which gives the worker sufficient time to actuate an emergency stop device before the robot can reach the person. A General Electric P-50 robot was programmed to provide the experimental situation. Nine subjects were tested, all in the age range 20–30. The subjects were male volunteers, not currently working in a job involving robot programming or maintenance.

scholarly journals Communicating and controlling robot arm motion intent through mixed-reality head-mounted displays

2019 ◽  
Vol 38 (12-13) ◽  
pp. 1513-1526 ◽  
Author(s):  
Eric Rosen ◽  
David Whitney ◽  
Elizabeth Phillips ◽  
Gary Chien ◽  
James Tompkin ◽  
...  
Keyword(s):  
Mixed Reality ◽  
World View ◽  
Collaborative Work ◽  
Robot Motion ◽  
Robot Arm ◽  
Verbal Cues ◽  
Head Mounted Display ◽  
Head Mounted Displays ◽  
Arm Motion ◽  
Increase In Accuracy

Efficient motion intent communication is necessary for safe and collaborative work environments with co-located humans and robots. Humans efficiently communicate their motion intent to other humans through gestures, gaze, and other non-verbal cues, and can replan their motions in response. However, robots often have difficulty using these methods. Many existing methods for robot motion intent communication rely on 2D displays, which require the human to continually pause their work to check a visualization. We propose a mixed-reality head-mounted display (HMD) visualization of the intended robot motion over the wearer’s real-world view of the robot and its environment. In addition, our interface allows users to adjust the intended goal pose of the end effector using hand gestures. We describe its implementation, which connects a ROS-enabled robot to the HoloLens using ROS Reality, using MoveIt for motion planning, and using Unity to render the visualization. To evaluate the effectiveness of this system against a 2D display visualization and against no visualization, we asked 32 participants to label various arm trajectories as either colliding or non-colliding with blocks arranged on a table. We found a 15% increase in accuracy with a 38% decrease in the time it took to complete the task compared with the next best system. These results demonstrate that a mixed-reality HMD allows a human to determine where the robot is going to move more quickly and accurately than existing baselines.

Automatic interpolation algorithm for NURBS trajectory of shoe sole spraying based on 7-DOF robot

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gaoping Xu ◽  
Hao Zhang ◽  
Zhuo Meng ◽  
Yize Sun
Keyword(s):  
Local Maximum ◽  
Good Effect ◽  
Robot Motion ◽  
Motion Trajectory ◽  
Interpolation Algorithm ◽  
Robot Arm ◽  
Joint Movement ◽  
Content Type ◽  
Nurbs Curves ◽  
Acceleration And Deceleration

PurposeThe purpose of this paper is to propose an automatic interpolation algorithm for robot spraying trajectories based on cubic Non-Uniform Rational B-Splines (NURBS) curves, to solve the problem of sparse and incomplete trajectory points of the head and heel of the shoe sole when extracting robot motion trajectories using structured-light 3D cameras and to ensure the robot joints move smoothly, so as to achieve a good effect of automatic spraying of the shoe sole with a 7-degree-of-freedom (DOF) robot.Design/methodology/approachFirstly, the original shoe sole edge trajectory position points acquired by the 3D camera are fitted with NURBS curves. Then, the velocity constraint at the local maximum of the trajectory curvature is used as the reference for curve segmentation and S-shaped acceleration and deceleration planning. Immediately, real-time interpolation is performed in the time domain to obtain the position and orientation of each point of the robot motion trajectory. Finally, the inverse kinematics of the anthropomorphic motion of the 7-DOF robot arm is used to obtain the joint motion trajectory.FindingsThe simulation and experiment prove that the shoe sole spraying trajectory is complete, the spraying effect is good and the robot joint movement is smooth, which show that the algorithm is feasible.Originality/valueThis study is of good practical value for improving the quality of automated shoe sole spraying, and it has wide applicability for different shoe sole shapes.

Robot Motion and Task Planning:Simulation and Programming of a Robot Arm

1987 ◽  
Vol 16 (3) ◽  
pp. 385-398 ◽  
Author(s):  
Iqbal Tabani ◽  
Akbar Montaser
Keyword(s):  
Robot Motion ◽  
Robot Arm ◽  
And Task

scholarly journals Dynamic manipulation of unknown string by robot arm: Realizing momentary string shapes

2020 ◽  
Author(s):  
Kenta Tabata ◽  
Hiroaki Seki ◽  
Tokuo Tsuji ◽  
Tatsuhiro Hiramitsu ◽  
Masatosh Hikizu
Keyword(s):  
Angular Velocity ◽  
High Speed ◽  
3D Model ◽  
String Model ◽  
Robot Motion ◽  
Robot Arm ◽  
Velocity Data ◽  
Motion Generation ◽  
Motion Data ◽  
Dynamic Manipulation

Abstract In this paper we propose dynamic manipulation for flexible object by using high speed robot arm. We consider dynamic manipulation for unknown string and describe how to manipulete it. Paticulary, we focus on the achived momentary string shapes. For example, momentary string shapes is like a J , C or d. In our strategy for dynamic manipulation of unknown string, manipulation is achieved through repeating 3steps: manipulation of string by robot arm, string parameter estimation. A string is described as the physical-dased 3D model. And ,motion data for robot arm is given as each joint angular velocity data. For simulation of motion, we input the each joint angular velocity data,and initial paramaretars of modeled string.This simulation calculate not only the motion of robot arm but also motion of modeled ropes which occured by robot motion. Parametar estimation is to string parametar by comparing image of the real manipulation with string model and motion generation by estimated model. Repeatly each step, we realize dynamic manipulation of unknown string. Finaly, we show the some experiment of dynamic manipulation ,and we demonstrate effective of parametar estimation and validity.

Adaptive arm motion generation of humanoid robot operating in dynamic environments

2014 ◽  
Vol 41 (2) ◽  
pp. 124-134 ◽  
Author(s):  
Zulkifli Mohamed ◽  
Mitsuki Kitani ◽  
Genci Capi
Keyword(s):  
Humanoid Robot ◽  
Dynamic Environments ◽  
Robot Motion ◽  
Robot Arm ◽  
Objective Functions ◽  
Motion Generation ◽  
Content Type ◽  
Neural Controllers ◽  
Wide Range ◽  
Arm Motion

Purpose – The purpose of this paper is to compare the performance of the robot arm motion generated by neural controllers in simulated and real robot experiments. Design/methodology/approach – The arm motion generation is formulated as an optimization problem. The neural controllers generate the robot arm motion in dynamic environments optimizing three different objective functions; minimum execution time, minimum distance and minimum acceleration. In addition, the robot motion generation in the presence of obstacles is also considered. Findings – The robot is able to adapt its arm motion generation based on the specific task, reaching the goal position in simulated and experimental tests. The same neural controller can be employed to generate the robot motion for a wide range of initial and goal positions. Research limitations/implications – The motion generated yield good results in both simulation and experimental environments. Practical implications – The robot motion is generated based on three different objective functions that are simultaneously optimized. Therefore, the humanoid robot can perform a wide range of tasks in real-life environments, by selecting the appropriate motion. Originality/value – A new method for adaptive arm motion generation of a mobile humanoid robot operating in dynamic human and industrial environments.

Sign in / Sign up

Export Citation Format

Share Document