Proceedings ArticleDOI
Vision-based predictive assist control on master-slave systems
Akio Namiki,Yosuke Matsumoto,Tomohiro Maruyama,Yang Liu +3 more
- pp 5357-5362
TLDR
This paper tackles a reaching task performed by a master-slave robot and proposes an operation assist algorithm based on visual feedback control that consists of visual object recognition for a slave robot, prediction of the operator's motion by a particle filter, and operation assistance of the reaching motion.Abstract:
In this paper, we propose a method for improving the maneuverability of master-slave systems. We aim at reproducing human skillfulness and dynamic performance in master-slave robots by using assist control for human operators. In this paper, we tackle a reaching task performed by a master-slave robot and propose an operation assist algorithm based on visual feedback control. The algorithm consists of visual object recognition for a slave robot, prediction of the operator's motion by a particle filter, estimation of the operator's intention, and operation assistance of the reaching motion. We verified the validity of the proposed system in experiments.read more
Citations
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Proceedings ArticleDOI
Using dVRK teleoperation to facilitate deep learning of automation tasks for an industrial robot
TL;DR: DY-Teleop, an interface between the da Vinci master manipulators and an ABB YuMi industrial robot to facilitate the collection of time-synchronized images and robot states for deep learning of automation tasks involving deformation and dynamic contact is presented.
Proceedings ArticleDOI
Prediction of Human Arm Target for Robot Reaching Movements
Chiara Talignani Landi,Yujiao Cheng,Federica Ferraguti,Marcello Bonfe,Cristian Secchi,Masayoshi Tomizuka +5 more
TL;DR: A human-arm prediction algorithm that allows to infer if the human operator is moving towards the robot to intentionally interact with it and obtained a reliable prediction of the human hand trajectory and final target in a short amount of time.
Journal ArticleDOI
A Target-Guided Telemanipulation Architecture for Assisted Grasping
TL;DR: This letter proposes a novel technique to assist the operators in reaching and manipulation of objects with one or two arms, combining local visual perception and operator’s action monitoring, and confirms the potential of the proposed framework in terms of success rate and operator effort.
Book ChapterDOI
WAREC-1 – A Four-Limbed Robot with Advanced Locomotion and Manipulation Capabilities
Kenji Hashimoto,Takashi Matsuzawa,Xiao Sun,Tomofumi Fujiwara,Xixun Wang,Yasuaki Konishi,Noritaka Sato,Takahiro Endo,Fumitoshi Matsuno,Naoyuki Kubota,Yuichiro Toda,Naoyuki Takesue,Kazuyoshi Wada,Tetsuya Mouri,Haruhisa Kawasaki,Akio Namiki,Yang Liu,Atsuo Takanishi,Satoshi Tadokoro +18 more
TL;DR: This chapter introduces a novel four-limbed robot, WAREC-1, that has advanced locomotion and manipulation capability with versatile locomotion styles, which enables the robot to move on rubble piles by creeping on its stomach.
Journal ArticleDOI
Assist system for remote manipulation of electric drills by the robot “WAREC-1R” using deep reinforcement learning
TL;DR: An assist system for a four-limbed robot is proposed for remote operation of reaches and grasping electric drills using deep reinforcement learning and the increase of success rate for reaching and grasping is verified and the decrease in both physical and mental workload of the operator is validated by the index of NASA-TLX.
References
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TL;DR: The beneficial effects of corrupting the link between operator and remote environment by introducing abstract perceptual information into the interface called virtual fixtures are described.
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Robonaut: NASA's space humanoid
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Proceedings ArticleDOI
Human-robot cooperative manipulation with motion estimation
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