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Learning Multi-Arm Manipulation Through Collaborative Teleoperation
[article]
2020
arXiv
pre-print
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Imitation Learning (IL) is a powerful paradigm to teach robots to perform manipulation tasks by allowing them to learn from human demonstrations collected via teleoperation, but has mostly been limited ...
To address these challenges, we present Multi-Arm RoboTurk (MART), a multi-user data collection platform that allows multiple remote users to simultaneously teleoperate a set of robotic arms and collect ...
Ajay Mandlekar acknowledges the support of the Department of Defense (DoD) through the NDSEG program. ...
arXiv:2012.06738v1
fatcat:lawzan47v5elbbwrtd2exijt5a
An adjustable autonomy paradigm for adapting to expert-novice differences
2013
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Multi-robot manipulation tasks are challenging for robots to complete in an entirely autonomous way due to the perceptual and cognitive requirements of grasp planning, necessitating the development of ...
fashion to manipulate objects without dropping them. ...
The goal of this process was to learn a model of user competence on the three axes of navigation, manipulation, and collaboration. ...
doi:10.1109/iros.2013.6696571
dblp:conf/iros/LewisTS13
fatcat:jguos4oqsfbovf67vdxg4lgjju
The AEROARMS Project: Aerial Robots with Advanced Manipulation Capabilities for Inspection and Maintenance
2018
IEEE robotics & automation magazine
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It presents aerial robotic manipulators with dual arms and multi-directional thrusters. ...
The lessons learned in the application to outdoor aerial manipulation for inspection and maintenance are pointed out. ...
Fig. 1 . 1 AEROARMS platforms: (a) Multi-directional thrust hexarotor with a rigidly attached end-effector; (b) Multi-directional thrust octorotor with an inspection arm; (c) Aerial dual-arms manipulator ...
doi:10.1109/mra.2018.2852789
fatcat:kaekerewqvdahcwq7grccmhjt4
Two hands are better than one: Assisting users with multi-robot manipulation tasks
2011
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Multi-robot manipulation, where two or more robots cooperatively grasp and move objects, is extremely challenging due to the necessity of tightly coupled temporal coordination between the robots. ...
In this paper, we propose an approach for semi-autonomously performing multi-robot manipulation tasks and demonstrate how our user interface reduces both task completion time and the number of dropped ...
In these modes, the unmanaged robot attempts to learn through demonstration the intent of the user by monitoring the command history of the teleoperated robot. ...
doi:10.1109/iros.2011.6048391
fatcat:ihferur76rar3gq4ufq6u36vyi
Two hands are better than one: Assisting users with multi-robot manipulation tasks
2011
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Multi-robot manipulation, where two or more robots cooperatively grasp and move objects, is extremely challenging due to the necessity of tightly coupled temporal coordination between the robots. ...
In this paper, we propose an approach for semi-autonomously performing multi-robot manipulation tasks and demonstrate how our user interface reduces both task completion time and the number of dropped ...
In these modes, the unmanaged robot attempts to learn through demonstration the intent of the user by monitoring the command history of the teleoperated robot. ...
doi:10.1109/iros.2011.6094815
dblp:conf/iros/LewisS11
fatcat:e6qcmx3gcbciflmu6inagdymji
A Systematic Review of Virtual Reality Interfaces for Controlling and Interacting with Robots
2020
Applied Sciences
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[36] also uses machine learning to improve teleoperation, but their focus is on a predict-then-blend framework to aid the operator in dual-arm robot manipulation tasks. ...
Instead of directly tracking an operator's arm pose, refs. [34, 35] both use machine learning techniques to learn a model that will map user input to robot motion in VR teleoperation interfaces. ...
doi:10.3390/app10249051
fatcat:p4aprukftnfehpfkz25ruzn2em
An Industrial Self-Learning Robotic Platform Solution for Smart Factories Industrial Applications Using Machine and Deep Imitation Learning
[chapter]
2021
Advances in Transdisciplinary Engineering
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There are two different methods of machine learning used in industrial collaborative robotics systems, Computer Vision Machine Learning and Imitation Learning. ...
A self-learning robotic system using deep imitation learning can reduce working time and give a less human error when performing high-precision processes. ...
Recently, the self-learning robotic arm using the imitation learning method has been used for trajectory planning of manipulators placed on small spacecraft. ...
doi:10.3233/atde210023
fatcat:vrrky7wxhvgftlkyy7pmjesio4
Dexterous telemanipulation with a multi-touch interface
2012
2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)
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Robust manipulation with a dexterous robot hand is a grand challenge of robotics. Impressive levels of dexterity can be achieved through teleoperation. ...
Our key insight is that dexterous grasping and manipulation interactions frequently focus on precise control of the fingertips in a plane. ...
(ARM-S). ...
doi:10.1109/humanoids.2012.6651531
dblp:conf/humanoids/TohHLBZP12
fatcat:4dh3h54nl5agvbmlezczohnla4
Towards 5G Enabled Tactile Robotic Telesurgery
[article]
2018
arXiv
pre-print
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better understanding of the characteristics of robotic telesurgical system, and the limiting factors, the possible telesurgery services and the communication quality of service (QoS) requirements of the multi-modal ...
Two geographically separated surgeons can collaborate in one surgery, i.e., manipulating the teleoperator remotely using a dual console which is available in the da Vinci SI Surgical System. ...
In telesurgergy, the master console and teleoperator will be connected by reliable high speed communication network to transport the real-time manipulation commands and multi-modal sensory data. ...
arXiv:1803.03586v1
fatcat:sohmkhvkhzahvef6qofer6oq3i
Neural-Learning Trajectory Tracking Control of Flexible-Joint Robot Manipulators with Unknown Dynamics
[article]
2019
arXiv
pre-print
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However, some collaborative robots sacrifice precision for safety, particular for high motion speed. ...
We consider two approaches to improve the trajectory tracking performance through feedforward compensation. ...
RELATED WORK There have been a lot of works for improving trajectory tracking performance of robot manipulators through controllers design based on learning dynamics models or inverse dynamics through ...
arXiv:1908.03269v1
fatcat:3zfgxiddojbijkja3elu27uo7q
DULA: A Differentiable Ergonomics Model for Postural Optimization in Physical HRI
[article]
2021
arXiv
pre-print
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We highlight DULA's strength in a demonstration of gradient-based postural optimization for a simulated teleoperation task. ...
In order to retain assessment quality, while improving computational considerations, we introduce DULA, a differentiable and continuous ergonomics model learned to replicate the popular and scientifically ...
We additionally define task parameters based on the RULA worksheet-the frequency of the arm and body motions; type and maximum load on the arm and body; neck angle; and whether any legs, feet, or arms ...
arXiv:2107.06875v1
fatcat:fgn3enmnwnayzeamgoiplw3vma
Learning Cooperative Dynamic Manipulation Skills from Human Demonstration Videos
[article]
2022
arXiv
pre-print
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This article proposes a method for learning and robotic replication of dynamic collaborative tasks from offline videos. ...
To achieve this goal, we decode important dynamic information, such as the Configuration Dependent Stiffness (CDS), which reveals the contribution of arm pose to the arm endpoint stiffness, from a three-dimensional ...
., through an optimisation problem or reinforcement learning), but instead can be demonstrated. ...
arXiv:2204.04003v1
fatcat:2fdlyus6zfgvtftuf3kouoowfy
Ergonomically Intelligent Physical Human-Robot Interaction: Postural Estimation, Assessment, and Optimization
[article]
2021
arXiv
pre-print
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We use DULA in postural optimization for physical human-robot interaction tasks such as co-manipulation and teleoperation. We evaluate our framework through human and simulation experiments. ...
Their arm model only includes the shoulder and elbow and not the wrist. We use this learned network for checking the validity of the arm posture. ...
Industry 4.0 initiative (Gorecky et al. 2014 ) and the development of collaborative workplaces where smart agents (e.g., collaborative robots (Sherwani, Asad, and Ibrahim 2020) ) physically collaborate ...
arXiv:2108.05971v2
fatcat:iafyyu2ynjfh5li6lepjp3pw7i
An Application-Based Review of Haptics Technology
2021
Robotics
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In general, haptic technology can be implemented in different applications such as gaming, teleoperation, medical surgeries, augmented reality (AR), and virtual reality (VR) devices. ...
Recent technological development has led to the invention of different designs of haptic devices, electromechanical devices that mediate communication between the user and the computer and allow users to manipulate ...
Haptic devices can provide the sense of touch to the operators while manipulating a virtual object or an actual object remotely through a teleoperation system. ...
doi:10.3390/robotics10010029
fatcat:zgxogdch7rbgnka2ejt7wsuwfi
Robust and Dexterous Dual-arm Tele-Cooperation using Fractal Impedance Control
[article]
2021
arXiv
pre-print
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and teleoperation applications. ...
The results confirmed that the proposed method can enhance the robustness significantly and allow switching tasks freely between manipulation, human-robot cooperation and teleoperation without the need ...
The fifth experiment involves two scenarios of humanrobot collaboration with the robot arms moving autonomously using the manipulation controller in the proposed architecture Figure 2 . ...
arXiv:2108.04567v1
fatcat:t2q3m7rytjfqzl6rpwdziohhwu
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