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Soft robotic manipulation
Soft robotic manipulation
How to manipulate an object under uncertainty with robots?
Kazutoshi Tanaka
Jul 19, 2021
TRANS-AM: Transfer Learning by Aggregating Dynamics Models for Soft Robotic Assembly
TRANS-AM: Transfer Learning by Aggregating Dynamics Models for Soft Robotic Assembly
We are thrilled to share that our project on transfer RL has been accepted to The 2021 International Conference on Robotics and Automation…
Kazutoshi Tanaka
Mar 24, 2021
Learning Soft Robotic Assembly Tasks with a Handful of Trials
Learning Soft Robotic Assembly Tasks with a Handful of Trials
We would like to introduce our project about learning assembly tasks with soft robots, which has been accepted to IEEE International…
Masashi Hamaya
May 31, 2020
An analytical diabolo model for robotic learning and control
An analytical diabolo model for robotic learning and control
At OMRON SINIC X, we made two robot arms play diabolo and are preparing to release the simulation model, dataset and control algorithm.
Felix von Drigalski
Nov 20, 2020
What is In-Hand Pose Estimation?
What is In-Hand Pose Estimation?
A robot’s representation of its environment is never perfect. When the robot grasps an object, there will generally be a slight offset, so…
Felix von Drigalski
May 31, 2020
OMRON SINIC X at ICRA 2021
OMRON SINIC X at ICRA 2021
The International Conference on Robotics and Automation (ICRA) is one of the top-tier conferences in robotics. At ICRA 2021, OMRON SINIC X…
Kazutoshi Tanaka
May 30, 2021
World MoveIt Day 2019 @ OMRON SINIC X
World MoveIt Day 2019 @ OMRON SINIC X
At OMRON SINIC X, we use MoveIt to work with our collaborators in universities and research institutes and plan high-level operations. For…
Felix von Drigalski
Nov 27, 2019
Transfer Learning
Transfer Learning
How to get your models working easily in new environments?
Ryo Yonetani
Jul 12, 2021
Noisy Universal Domain Adaptation (CVPR2021)
Noisy Universal Domain Adaptation (CVPR2021)
We are delighted to announce that one of our papers got accepted to the IEEE/CVF Conference on Computer Vision and Pattern Recognition…
Atsushi Hashimoto
Apr 4, 2021
Adaptive Distillation for Decentralized Learning from Heterogeneous Clients (ICPR’20)
Adaptive Distillation for Decentralized Learning from Heterogeneous Clients (ICPR’20)
We are pleased to announce that our recent work on federated learning for heterogeneous clients will be presented at the International…
Ryo Yonetani
Jan 3, 2021
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse…
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse…
We are thrilled to share that our project on transfer RL has been accepted to the International Joint Conference on Artificial…
Ryo Yonetani
May 7, 2020
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