Collaborative Autonomy between High-level Behaviors and Human Operators for Remote Manipulation Tasks using Different Humanoid Robots

2016 ◽  
Vol 34 (2) ◽  
pp. 333-358 ◽  
Author(s):  
Alberto Romay ◽  
Stefan Kohlbrecher ◽  
Alexander Stumpf ◽  
Oskar von Stryk ◽  
Spyros Maniatopoulos ◽  
...  
Keyword(s):  
Humanoid Robots ◽  
Remote Manipulation ◽  
Human Operators ◽  
High Level ◽  
Collaborative Autonomy

Exploring The Effect of Visual Information Degradation on Human Perception and Performance In A Human-Telerobot System

2020 ◽  
Vol 64 (1) ◽  
pp. 1302-1307
Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall
Keyword(s):  
Visual Information ◽  
Human Perception ◽  
Low Level ◽  
Hit Rate ◽  
Word Level ◽  
Level Of Automation ◽  
Significant Difference ◽  
Human Operators ◽  
And Performance ◽  
High Level

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.

scholarly journals Transportable open-source application program interface and user interface for generic humanoids: TOUGH

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092160
Author(s):  
Vinayak Jagtap ◽  
Shlok Agarwal ◽  
Ameya Wagh ◽  
Michael Gennert
Keyword(s):  
User Interface ◽  
Open Source ◽  
Humanoid Robots ◽  
Application Program Interface ◽  
Sensors And Actuators ◽  
Seamless Integration ◽  
Application Program ◽  
Diverse Field ◽  
High Level ◽  
Program Interface

Humanoid robotics is a complex and highly diverse field. Humanoid robots may have dozens of sensors and actuators that together realize complicated behaviors. Adding to the complexity is that each type of humanoid has unique application program interfaces, thus software written for one humanoid does not easily transport to others. This article introduces the transportable open-source application program interface and user interface for generic humanoids, a set of application program interfaces that simplifies the programming and operation of diverse humanoid robots. These application program interfaces allow for quick implementation of complex tasks and high-level controllers. Transportable open-source application program interface and user interface for generic humanoids has been developed for, and tested on, Boston Dynamics’ Atlas V5 and NASA’s Valkyrie R5 robots. It has proved successful for experiments on both robots in simulation and hardware, demonstrating the seamless integration of manipulation, perception, and task planning. To encourage the rapid adoption of transportable open-source application program interface and user interface for generic humanoids for education and research, the software is available as Docker images, which enable quick setup of multiuser simulation environments.

scholarly journals A Robotic Cognitive Architecture for Slope and Dam Inspections

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4579 ◽  
Author(s):  
Milena F. Pinto ◽  
Leonardo M. Honorio ◽  
Aurélio Melo ◽  
Andre L. M. Marcato
Keyword(s):  
Decision Making ◽  
Cognitive Architecture ◽  
Electrical Power ◽  
Data Gathering ◽  
Path Following ◽  
Sensors And Actuators ◽  
Construction Enterprises ◽  
Performance Quality ◽  
Human Operators ◽  
High Level

Big construction enterprises, such as electrical power generation dams and mining slopes, demand continuous visual inspections. The sizes of these structures and the necessary level of detail in each mission requires a conflicting set of multi-objective goals, such as performance, quality, and safety. It is challenging for human operators, or simple autonomous path-following drones, to process all this information, and thus, it is common that a mission must be repeated several times until it succeeds. This paper deals with this problem by developing a new cognitive architecture based on a collaborative environment between the unmanned aerial vehicles (UAVs) and other agents focusing on optimizing the data gathering, information processing, and decision-making. The proposed architecture breaks the problem into independent units ranging from sensors and actuators up to high-level intelligence processes. It organizes the structures into data and information; each agent may request an individual behavior from the system. To deal with conflicting behaviors, a supervisory agent analyzes all requests and defines the final planning. This architecture enables real-time decision-making with intelligent social behavior among the agents. Thus, it is possible to process and make decisions about the best way to accomplish the mission. To present the methodology, slope inspection scenarios are shown.

Compensation for Object Motion in Remote Manipulation

1993 ◽  
Vol 5 (1) ◽  
pp. 66-72
Author(s):  
Kazuo Tani ◽  
Keyword(s):  
Computer Control ◽  
Operation Time ◽  
Computation Time ◽  
Experimental System ◽  
Object Motion ◽  
Moving Object ◽  
Remote Manipulation ◽  
Control Scheme ◽  
Computer Controlled ◽  
Human Operators

The goal of this project is the proposal of the concept of master/slave control with compensation for object motion in order to facilitate the manipulation of a moving object and the evaluation of the compensation by experimentally comparing the performance of the operator. An experimental system was constructed consisting of a master/slave manipulator, a moving table for the moving object, and a computer which controls both the manipulator and table. A computer control scheme for master/ slave and compensation for object motion was developed in consideration of the kinematics and dynamics of the manipulator. The computation time in this scheme was shown to be practical and permitted a system sampling time of 50 ms. Experiments were conducted with human operators performing manipulation tasks in computer controlled master/slave. Their performance was compared in three situations: no object motion, compensation for object motion, and no compensation. The comparison of the compensation and no compensation situations showed that compensation reduced the operation time by 26-41% in the peg moving task and increased the accuracy by two and a half times in rectangle tracing. However, in valve turning, significant improvement was not observed. Thus, it was concluded that compensation for object motion can significantly improve the performance of the human operator in certain kinds of tasks.

Whole-Body Balancing Walk Controller for Position Controlled Humanoid Robots

2016 ◽  
Vol 13 (01) ◽  
pp. 1650011 ◽  
Author(s):  
Seung-Joon Yi ◽  
Byoung-Tak Zhang ◽  
Dennis Hong ◽  
Daniel D. Lee
Keyword(s):  
Hierarchical Control ◽  
Humanoid Robots ◽  
Whole Body ◽  
Appropriate Behavior ◽  
Low Level ◽  
Push Recovery ◽  
Hierarchical Control Architecture ◽  
High Level ◽  
Experimental Trials ◽  
Decision Boundaries

Bipedal humanoid robots are intrinsically unstable against unforeseen perturbations. Conventional zero moment point (ZMP)-based locomotion algorithms can reject perturbations by incorporating sensory feedback, but they are less effective than the dynamic full body behaviors humans exhibit when pushed. Recently, a number of biomechanically motivated push recovery behaviors have been proposed that can handle larger perturbations. However, these methods are based upon simplified and transparent dynamics of the robot, which makes it suboptimal to implement on common humanoid robots with local position-based controllers. To address this issue, we propose a hierarchical control architecture. Three low-level push recovery controllers are implemented for position controlled humanoid robots that replicate human recovery behaviors. These low-level controllers are integrated with a ZMP-based walk controller that is capable of generating reactive step motions. The high-level controller constructs empirical decision boundaries to choose the appropriate behavior based upon trajectory information gathered during experimental trials. Our approach is evaluated in physically realistic simulations and on a commercially available small humanoid robot.

scholarly journals Whole-Body Operational Space Control for Locomotion and Manipulation

2015 ◽  
Vol 137 (06) ◽  
pp. S2-S6
Author(s):  
Luis Sentis
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Humanoid Robots ◽  
Rigid Body Dynamics ◽  
Joint Torque ◽  
Whole Body ◽  
Operational Space ◽  
Body Dynamics ◽  
Service Oriented ◽  
High Level

This article discusses the various researches being undertaken to study and develop Whole-Body Operational Space Control (WBOSC). The WBOSC emerges as a capable framework for real-time unified control of motion and force of humanoid robots. It could theoretically outperform high-speed industrial manipulators while providing the grounds for new types of service-oriented applications that require contact, by exploiting the rigid body dynamics of systems. By relying on joint torque sensors, WBOSC opens up the potential to interact with the physical environment using any part of the robot’s body while regulating the effective mechanical impedances to safe values. With ControlIt!, the developers provide a strict and easy way to use the WBOSC API consisting of compound tasks which define the operational space, and constraint sets that define the contacts with the environment as well as dependent degrees of freedom. ControlIt! is easy to connect to high level planners.

scholarly journals DAQExpert the service to increase CMS data-taking efficiency

2020 ◽  
Vol 245 ◽  
pp. 01028
Author(s):  
Gilbert Badaro ◽  
Ulf Behrens ◽  
James Branson ◽  
Philipp Brummer ◽  
Sergio Cittolin ◽  
...  
Keyword(s):  
Human Error ◽  
Expert Knowledge ◽  
Critical Role ◽  
Operational Experience ◽  
Software Failure ◽  
Level Trigger ◽  
Cms Experiment ◽  
Human Operators ◽  
High Level ◽  
In The Beginning

The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at the LHC is a complex system responsible for the data readout, event building and recording of accepted events. Its proper functioning plays a critical role in the data-taking efficiency of the CMS experiment. In order to ensure high availability and recover promptly in the event of hardware or software failure of the subsystems, an expert system, the DAQ Expert, has been developed. It aims at improving the data taking efficiency, reducing the human error in the operations and minimising the on-call expert demand. Introduced in the beginning of 2017, it assists the shift crew and the system experts in recovering from operational faults, streamlining the post mortem analysis and, at the end of Run 2, triggering fully automatic recovery without human intervention. DAQ Expert analyses the real-time monitoring data originating from the DAQ components and the high-level trigger updated every few seconds. It pinpoints data flow problems, and recovers them automatically or after given operator approval. We analyse the CMS downtime in the 2018 run focusing on what was improved with the introduction of automated recovery; present challenges and design of encoding the expert knowledge into automated recovery jobs. Furthermore, we demonstrate the web-based, ReactJS interfaces that ensure an effective cooperation between the human operators in the control room and the automated recovery system. We report on the operational experience with automated recovery.

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