scholarly journals Human-Robot Interaction With Robust Prediction of Movement Intention Surpasses Manual Control

2021 ◽  
Vol 15 ◽  
Author(s):  
Sebastijan Veselic ◽  
Claudio Zito ◽  
Dario Farina
Keyword(s):  
Degrees Of Freedom ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Manual Control ◽  
Robot Interaction ◽  
User Intention ◽  
Cognitive Capability ◽  
User Awareness ◽  
Novel Applications ◽  
Robust Prediction

Physical human-robot interaction (pHRI) enables a user to interact with a physical robotic device to advance beyond the current capabilities of high-payload and high-precision industrial robots. This paradigm opens up novel applications where a the cognitive capability of a user is combined with the precision and strength of robots. Yet, current pHRI interfaces suffer from low take-up and a high cognitive burden for the user. We propose a novel framework that robustly and efficiently assists users by reacting proactively to their commands. The key insight is to include context- and user-awareness in the controller, improving decision-making on how to assist the user. Context-awareness is achieved by inferring the candidate objects to be grasped in a task or scene and automatically computing plans for reaching them. User-awareness is implemented by facilitating the motion toward the most likely object that the user wants to grasp, as well as dynamically recovering from incorrect predictions. Experimental results in a virtual environment of two degrees of freedom control show the capability of this approach to outperform manual control. By robustly predicting user intention, the proposed controller allows subjects to achieve superhuman performance in terms of accuracy and, thereby, usability.

scholarly journals Human-Robot Interaction with Robust Prediction of Movement Intention Surpasses Manual Control

2020 ◽  
Author(s):  
Sebastijan Veselic ◽  
Claudio Zito ◽  
Dario Farina
Keyword(s):  
Degrees Of Freedom ◽  
Linear Time ◽  
Open Loop ◽  
Human Robot Interaction ◽  
Manual Control ◽  
Reach To Grasp ◽  
Robot Interaction ◽  
Loop Control ◽  
User Awareness ◽  
Improving Accuracy

Designing robotic assistance devices for manipulation tasks is challenging. This work aims at improving accuracy and usability of physical human-robot interaction (pHRI) where a user interacts with a physical robotic device (e.g., a human operated manipulator or exoskeleton) by transmitting signals which need to be interpreted by the machine. Typically these signals are used as an open-loop control, but this approach has several limitations such as low take-up and high cognitive burden for the user. In contrast, a control framework is proposed that can respond robustly and efficiently to intentions of a user by reacting proactively to their commands. The key insight is to include context- and user-awareness in the controller, improving decision making on how to assist the user. Context-awareness is achieved by creating a set of candidate grasp targets and reach-to grasp trajectories in a cluttered scene. User-awareness is implemented as a linear time-variant feedback controller (TV-LQR) over the generated trajectories to facilitate the motion towards the most likely intention of a user. The system also dynamically recovers from incorrect predictions. Experimental results in a virtual environment of two degrees of freedom control show the capability of this approach to outperform manual control. By robustly predicting the user’s intention, the proposed controller allows the subject to achieve superhuman performance in terms of accuracy and thereby usability.

Human–robot interaction via voice-controllable intelligent user interface

Robotica ◽  
2007 ◽  
Vol 25 (5) ◽  
pp. 521-527 ◽  
Author(s):  
Harsha Medicherla ◽  
Ali Sekmen
Keyword(s):  
User Interface ◽  
User Interfaces ◽  
Spatial Reasoning ◽  
User Preferences ◽  
Human Robot Interaction ◽  
Manual Control ◽  
Reasoning Ability ◽  
Robot Interaction ◽  
Intelligent User Interface ◽  
Voice Control

SUMMARYAn understanding of how humans and robots can successfully interact to accomplish specific tasks is crucial in creating more sophisticated robots that may eventually become an integral part of human societies. A social robot needs to be able to learn the preferences and capabilities of the people with whom it interacts so that it can adapt its behaviors for more efficient and friendly interaction. Advances in human– computer interaction technologies have been widely used in improving human–robot interaction (HRI). It is now possible to interact with robots via natural communication means such as speech. In this paper, an innovative approach for HRI via voice-controllable intelligent user interfaces is described. The design and implementation of such interfaces are described. The traditional approaches for human–robot user interface design are explained and the advantages of the proposed approach are presented. The designed intelligent user interface, which learns user preferences and capabilities in time, can be controlled with voice. The system was successfully implemented and tested on a Pioneer 3-AT mobile robot. 20 participants, who were assessed on spatial reasoning ability, directed the robot in spatial navigation tasks to evaluate the effectiveness of the voice control in HRI. Time to complete the task, number of steps, and errors were collected. Results indicated that spatial reasoning ability and voice-control were reliable predictors of efficiency of robot teleoperation. 75% of the subjects with high spatial reasoning ability preferred using voice-control over manual control. The effect of spatial reasoning ability in teleoperation with voice-control was lower compared to that of manual control.

Special Issue on Human-Robot Interaction in Close Distance

2020 ◽  
Vol 32 (1) ◽  
pp. 7-7
Author(s):  
Masahiro Shiomi ◽  
Hidenobu Sumioka ◽  
Hiroshi Ishiguro
Keyword(s):  
Physical Distance ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Physical Contact ◽  
Special Issue ◽  
Robot Interaction ◽  
Behavior Design ◽  
Physical Interactions ◽  
Close Distance

As social robot research is advancing, the interaction distance between people and robots is decreasing. Indeed, although we were once required to maintain a certain physical distance from traditional industrial robots for safety, we can now interact with social robots in such a close distance that we can touch them. The physical existence of social robots will be essential to realize natural and acceptable interactions with people in daily environments. Because social robots function in our daily environments, we must design scenarios where robots interact closely with humans by considering various viewpoints. Interactions that involve touching robots influence the changes in the behavior of a person strongly. Therefore, robotics researchers and developers need to design such scenarios carefully. Based on these considerations, this special issue focuses on close human-robot interactions. This special issue on “Human-Robot Interaction in Close Distance” includes a review paper and 11 other interesting papers covering various topics such as social touch interactions, non-verbal behavior design for touch interactions, child-robot interactions including physical contact, conversations with physical interactions, motion copying systems, and mobile human-robot interactions. We thank all the authors and reviewers of the papers and hope this special issue will help readers better understand human-robot interaction in close distance.

scholarly journals Practical Aspects of Model-Based Collision Detection

2020 ◽  
Vol 7 ◽  
Author(s):  
Shamil Mamedov ◽  
Stanislav Mikhel
Keyword(s):  
Collision Detection ◽  
Model Identification ◽  
Computation Time ◽  
Human Robot Interaction ◽  
Observer Design ◽  
Industrial Robots ◽  
Robot Interaction ◽  
Model Based ◽  
Proprioceptive Sensors ◽  
The Relationship

Recently, with the increased number of robots entering numerous manufacturing fields, a considerable wealth of literature has appeared on the theme of physical human-robot interaction using data from proprioceptive sensors (motor or/and load side encoders). Most of the studies have then the accurate dynamic model of a robot for granted. In practice, however, model identification and observer design proceeds collision detection. To the best of our knowledge, no previous study has systematically investigated each aspect underlying physical human-robot interaction and the relationship between those aspects. In this paper, we bridge this gap by first reviewing the literature on model identification, disturbance estimation and collision detection, and discussing the relationship between the three, then by examining the practical sides of model-based collision detection on a case study conducted on UR10e. We show that the model identification step is critical for accurate collision detection, while the choice of the observer should be mostly based on computation time and the simplicity and flexibility of tuning. It is hoped that this study can serve as a roadmap to equip industrial robots with basic physical human-robot interaction capabilities.

scholarly journals HMM-based phoneme speech recognition system for the control and command of industrial robots

2021 ◽  
pp. 1-16
Author(s):  
Adwait Naik
Keyword(s):  
Speech Recognition ◽  
Degrees Of Freedom ◽  
Microphone Array ◽  
Predictive Coding ◽  
Recognition System ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Speech Recognition System ◽  
Linear Predictive Coding ◽  
Complex Sentences

In recent years, the integration of human-robot interaction with speech recognition has gained a lot of pace in the manufacturing industries. Conventional methods to control the robots include semi-autonomous, fully-autonomous, and wired methods. Operating through a teaching pendant or a joystick is easy to implement but is not effective when the robot is deployed to perform complex repetitive tasks. Speech and touch are natural ways of communicating for humans and speech recognition, being the best option, is a heavily researched technology. In this study, we aim at developing a stable and robust speech recognition system to allow humans to communicate with machines (roboticarm) in a seamless manner. This paper investigates the potential of the linear predictive coding technique to develop a stable and robust HMM-based phoneme speech recognition system for applications in robotics. Our system is divided into three segments: a microphone array, a voice module, and a robotic arm with three degrees of freedom (DOF). To validate our approach, we performed experiments with simple and complex sentences for various robotic activities such as manipulating a cube and pick and place tasks. Moreover, we also analyzed the test results to rectify problems including accuracy and recognition score.

scholarly journals HUMANOID LOCOMOTION MANIPULATED USING DYNAMIC FINGER GESTURES

2013 ◽  
pp. 170-173
Author(s):  
HARI KRISHNAN R ◽  
VALLIKANNU A. L
Keyword(s):  
Human Computer Interaction ◽  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Hand Motion ◽  
Computer Interaction

The fundamental technologies for Human-Computer Interaction are Hand motion tracking and Gesture Identification. The same technology has been adapted for Human-Robot Interaction. This paper discusses a natural methodology for Human-Robot Interaction. In the proposed system, the accelerometers at the fingers, tracks specific gestures. These gestures are identified by the controller, which in turn controls the actuators that results in Humanoid walking. The Humanoid under consideration has 8 Degrees of Freedom.

scholarly journals V2SOM: A Novel Safety Mechanism Dedicated to a Cobot’s Rotary Joints

Robotics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 18 ◽  
Author(s):  
Younsse Ayoubi ◽  
Med Laribi ◽  
Said Zeghloul ◽  
Marc Arsicault
Keyword(s):  
Good Control ◽  
Variable Stiffness ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Necessary Condition ◽  
Physical Interaction ◽  
Robot Interaction ◽  
Internal Damage ◽  
Low Stiffness ◽  
The Impact

Unlike “classical” industrial robots, collaborative robots, known as cobots, implement a compliant behavior. Cobots ensure a safe force control in a physical interaction scenario within unknown environments. In this paper, we propose to make serial robots intrinsically compliant to guarantee safe physical human–robot interaction (pHRI), via our novel designed device called V2SOM, which stands for Variable Stiffness Safety-Oriented Mechanism. As its name indicates, V2SOM aims at making physical human–robot interaction safe, thanks to its two basic functioning modes—high stiffness mode and low stiffness mode. The first mode is employed for normal operational routines. In contrast, the low stiffness mode is suitable for the safe absorption of any potential blunt shock with a human. The transition between the two modes is continuous to maintain a good control of the V2SOM-based cobot in the case of a fast collision. V2SOM presents a high inertia decoupling capacity which is a necessary condition for safe pHRI without compromising the robot’s dynamic performances. Two safety criteria of pHRI were considered for performance evaluations, namely, the impact force (ImpF) criterion and the head injury criterion (HIC) for, respectively, the external and internal damage evaluation during blunt shocks.

scholarly journals Development of Flexible Robot Skin for Safe and Natural Human–Robot Collaboration

Micromachines ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 576 ◽  
Author(s):  
Gaoyang Pang ◽  
Jia Deng ◽  
Fangjinhua Wang ◽  
Junhui Zhang ◽  
Zhibo Pang ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Percentage Change ◽  
Flexible Robot ◽  
Robot Interaction ◽  
Industrial Manufacturing ◽  
Collision Force ◽  
The One ◽  
Robot Skin

For industrial manufacturing, industrial robots are required to work together with human counterparts on certain special occasions, where human workers share their skills with robots. Intuitive human–robot interaction brings increasing safety challenges, which can be properly addressed by using sensor-based active control technology. In this article, we designed and fabricated a three-dimensional flexible robot skin made by the piezoresistive nanocomposite based on the need for enhancement of the security performance of the collaborative robot. The robot skin endowed the YuMi robot with a tactile perception like human skin. The developed sensing unit in the robot skin showed the one-to-one correspondence between force input and resistance output (percentage change in impedance) in the range of 0–6.5 N. Furthermore, the calibration result indicated that the developed sensing unit is capable of offering a maximum force sensitivity (percentage change in impedance per Newton force) of 18.83% N−1 when loaded with an external force of 6.5 N. The fabricated sensing unit showed good reproducibility after loading with cyclic force (0–5.5 N) under a frequency of 0.65 Hz for 3500 cycles. In addition, to suppress the bypass crosstalk in robot skin, we designed a readout circuit for sampling tactile data. Moreover, experiments were conducted to estimate the contact/collision force between the object and the robot in a real-time manner. The experiment results showed that the implemented robot skin can provide an efficient approach for natural and secure human–robot interaction.

Practical application of a safe human-robot interaction software

2020 ◽  
Vol 47 (3) ◽  
pp. 359-368 ◽  
Author(s):  
Mustafa Can Bingol ◽  
Omur Aydogmus
Keyword(s):  
Robot Manipulator ◽  
Industrial Robot ◽  
Wavelet Packet ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Robot Interaction ◽  
Content Type ◽  
Depth Sensors ◽  
Working Space ◽  
Vision Module

Purpose Because of the increased use of robots in the industry, it has become inevitable for humans and robots to be able to work together. Therefore, human security has become the primary noncompromising factor of joint human and robot operations. For this reason, the purpose of this study was to develop a safe human-robot interaction software based on vision and touch. Design/methodology/approach The software consists of three modules. Firstly, the vision module has two tasks: to determine whether there is a human presence and to measure the distance between the robot and the human within the robot’s working space using convolutional neural networks (CNNs) and depth sensors. Secondly, the touch detection module perceives whether or not a human physically touches the robot within the same work environment using robot axis torques, wavelet packet decomposition algorithm and CNN. Lastly, the robot’s operating speed is adjusted according to hazard levels came from vision and touch module using the robot’s control module. Findings The developed software was tested with an industrial robot manipulator and successful results were obtained with minimal error. Practical implications The success of the developed algorithm was demonstrated in the current study and the algorithm can be used in other industrial robots for safety. Originality/value In this study, a new and practical safety algorithm is proposed and the health of people working with industrial robots is guaranteed.

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