VTacArm. A Vision-based Tactile Sensing Augmented Robotic Arm with Application to Human-robot Interaction

2020 ◽  
Author(s):  
Yazhan Zhang ◽  
Guanlan Zhang ◽  
Yipai Du ◽  
Michael Yu Wang
Keyword(s):  
Human Robot Interaction ◽  
Robotic Arm ◽  
Tactile Sensing ◽  
Robot Interaction

scholarly journals Cable Tension Analysis Oriented the Enhanced Stiffness of a 3-DOF Joint Module of a Modular Cable-Driven Human-Like Robotic Arm

2020 ◽  
Vol 10 (24) ◽  
pp. 8871
Author(s):  
Kaisheng Yang ◽  
Guilin Yang ◽  
Chi Zhang ◽  
Chinyin Chen ◽  
Tianjiang Zheng ◽  
...  
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Human Robot Interaction ◽  
Robotic Arm ◽  
Robot Interaction ◽  
Cable Tension ◽  
Tension Distribution ◽  
Stiffness Model ◽  
Redundantly Actuated ◽  
Objective Function Values

Inspired by the structure of human arms, a modular cable-driven human-like robotic arm (CHRA) is developed for safe human–robot interaction. Due to the unilateral driving properties of the cables, the CHRA is redundantly actuated and its stiffness can be adjusted by regulating the cable tensions. Since the trajectory of the 3-DOF joint module (3DJM) of the CHRA is a curve on Lie group SO(3), an enhanced stiffness model of the 3DJM is established by the covariant derivative of the load to the displacement on SO(3). In this paper, we focus on analyzing the how cable tension distribution problem oriented the enhanced stiffness of the 3DJM of the CHRA for stiffness adjustment. Due to the complexity of the enhanced stiffness model, it is difficult to solve the cable tensions from the desired stiffness analytically. The problem of stiffness-oriented cable tension distribution (SCTD) is formulated as a nonlinear optimization model. The optimization model is simplified using the symmetry of the enhanced stiffness model, the rank of the Jacobian matrix and the equilibrium equation of the 3DJM. Since the objective function is too complicated to compute the gradient, a method based on the genetic algorithm is proposed for solving this optimization problem, which only utilizes the objective function values. A comprehensive simulation is carried out to validate the effectiveness of the proposed method.

Gestures Identification for Myoelectric Based Control of the Robotic Arm

2020 ◽  
Vol 22 (12) ◽  
Author(s):  
Adhau P ◽  
◽  
Kadwane S. G ◽  
Shital Telrandhe ◽  
Rajguru V. S ◽  
...  
Keyword(s):  
Neural Network ◽  
Human Body ◽  
Human Robot Interaction ◽  
Robotic Arm ◽  
Human Hand ◽  
Robot Interaction ◽  
The Neural Network

Human robot interaction have been ever the topic of research to research scholars owing to its importance to help humanity. Robust human interacting robot where commands from Electromyogram (EMG) signals is recently being investigated. This article involves study of motions a system that allows signals recorded directly from a human body and thereafter can be used for control of a small robotic arm. The various gestures are recognized by placing the electrodes or sensors on the human hand. These gestures are then identified by using neural network. The neural network will thus train the signals. The offline control of the arm is done by controlling the motors of the robotic arm.

Special issue on advances in tactile sensing and tactile-based human–robot interaction

2015 ◽  
Vol 63 ◽  
pp. 227-229 ◽  
Author(s):  
Fulvio Mastrogiovanni ◽  
Lorenzo Natale ◽  
Giorgio Cannata ◽  
Giorgio Metta
Keyword(s):  
Human Robot Interaction ◽  
Tactile Sensing ◽  
Special Issue ◽  
Robot Interaction

A Continuously Tunable Stiffness Arm With Cable-Driven Mechanisms for Safe Physical Human-Robot Interaction

2020 ◽  
Author(s):  
Yu She ◽  
Zhaoyuan Gu ◽  
Siyang Song ◽  
Hai-Jun Su ◽  
Junmin Wang
Keyword(s):  
Variable Stiffness ◽  
Human Robot Interaction ◽  
Robotic Arm ◽  
Robot Arm ◽  
Robot Interaction ◽  
Safety Issues ◽  
Compliant Joints ◽  
Mechanical Compliance ◽  
3D Printed ◽  
Tunable Stiffness

Abstract In this paper, we present a continuously tunable stiffness arm for safe physical human-robot interactions. Compliant joints and compliant links are two typical solutions to address safety issues for physical human-robot interaction via introducing mechanical compliance to robotic systems. While extensive studies explore variable stiffness joints/actuators, variable stiffness links for safe physical human-robot interactions are much less studied. This paper details the design and modeling of a compliant robotic arm whose stiffness can be continuously tuned via cable-driven mechanisms actuated by a single servo motor. Specifically, a 3D printed compliant robotic arm is prototyped and tested by static experiments, and an analytical model of the variable stiffness arm is derived and validated by testing. The results show that the lateral stiffness of the robot arm can achieve a variety of 221.26% given a morphing angle of 90°. The study demonstrates that the compliant link design could be a promising approach to address safety concerns for safe physical human-robot interactions.

Robot-to-human feedback and automatic object grasping using an RGB-D camera–projector system

Robotica ◽  
2017 ◽  
Vol 36 (2) ◽  
pp. 241-260 ◽  
Author(s):  
Jinglin Shen ◽  
Nicholas Gans
Keyword(s):  
Visual Attention ◽  
Visual Servoing ◽  
Robot Manipulator ◽  
Human Robot Interaction ◽  
Experimental Results ◽  
Robotic Arm ◽  
Depth Information ◽  
Robot Interaction ◽  
Attention Model ◽  
Robot Grasping

SUMMARYThis paper presents a novel system for human–robot interaction in object-grasping applications. Consisting of an RGB-D camera, a projector and a robot manipulator, the proposed system provides intuitive information to the human by analyzing the scene, detecting graspable objects and directly projecting numbers or symbols in front of objects. Objects are detected using a visual attention model that incorporates color, shape and depth information. The positions and orientations of the projected numbers are based on the shapes, positions and orientations of the corresponding objects. Users select a grasping target by indicating the corresponding number. Projected arrows are then created on the fly to guide a robotic arm to grasp the selected object using visual servoing and deliver the object to the human user. Experimental results are presented to demonstrate how the system is used in robot grasping tasks.

scholarly journals Does One Size Fit All? A Case Study to Discuss Findings of an Augmented Hands-Free Robot Teleoperation Concept for People with and without Motor Disabilities

Technologies ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 4
Author(s):  
Stephanie Arévalo Arboleda ◽  
Marvin Becker ◽  
Jens Gerken
Keyword(s):  
Augmented Reality ◽  
Human Robot Interaction ◽  
Robotic Arm ◽  
Robot Interaction ◽  
Robotic Arms ◽  
Motor Disabilities ◽  
Microsoft Hololens ◽  
Mixed Groups ◽  
Learning Points

Hands-free robot teleoperation and augmented reality have the potential to create an inclusive environment for people with motor disabilities. It may allow them to teleoperate robotic arms to manipulate objects. However, the experiences evoked by the same teleoperation concept and augmented reality can vary significantly for people with motor disabilities compared to those without disabilities. In this paper, we report the experiences of Miss L., a person with multiple sclerosis, when teleoperating a robotic arm in a hands-free multimodal manner using a virtual menu and visual hints presented through the Microsoft HoloLens 2. We discuss our findings and compare her experiences to those of people without disabilities using the same teleoperation concept. Additionally, we present three learning points from comparing these experiences: a re-evaluation of the metrics used to measure performance, being aware of the bias, and considering variability in abilities, which evokes different experiences. We consider these learning points can be extrapolated to carrying human–robot interaction evaluations with mixed groups of participants with and without disabilities.

ROBOTIC ARM COLLISION REACTION STRATEGIES FOR SAFE HUMAN–ROBOT INTERACTION WITHOUT TORQUE SENSORS

2019 ◽  
Vol 19 (07) ◽  
pp. 1940034 ◽  
Author(s):  
TIAN XU ◽  
JIZHUANG FAN ◽  
QIANQIAN FANG ◽  
JIE ZHAO ◽  
YANHE ZHU
Keyword(s):  
Collision Detection ◽  
Mechanical Impedance ◽  
Human Robot Interaction ◽  
Robotic Arm ◽  
Physical Interaction ◽  
Human Being ◽  
Robot Interaction ◽  
Motor Torque ◽  
Inertia Matrix ◽  
Generalized Momentum

Three kinds of collision reaction strategies for increasing safety during human and robot interactions without relying on torque sensors are proposed in this paper. In the proposed algorithms, motor torque is estimated by driver current. The generalized momentum observer is used for collision detection, which does not need joints acceleration information and calculates the inverse of the inertia matrix. Three different collision reaction strategies, going away, dragging by hands and mechanical impedance developed in this paper, aim to enhance safety to humans during physical interaction with robots. For verifying the efficiency of the proposed algorithms, experiments are tested between a 1-DOF manipulator system and a human being. At last, the experiments’ results show that the proposed collision reaction algorithms are effective.

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