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pro vyhledávání: '"Maeda, Guilherme"'
A problem that plagues robotic grasping is the misalignment of the object and gripper due to difficulties in precise localization, actuation, etc. Under-actuated robotic hands with compliant mechanisms are used to adapt and compensate for these inacc
Externí odkaz:
http://arxiv.org/abs/2309.08312
It is challenging to grasp numerous objects with varying sizes and shapes with a single robot hand. To address this, we propose a new robot hand called the 'F3 hand' inspired by the complex movements of human index finger and thumb. The F3 hand attem
Externí odkaz:
http://arxiv.org/abs/2206.06556
Teleoperation is often limited by the ability of an operator to react and predict the behavior of the robot as it interacts with the environment. For example, to grasp small objects on a table, the teleoperator needs to predict the position of the fi
Externí odkaz:
http://arxiv.org/abs/2205.07066
Autor:
Maeda, Guilherme
Movement primitives have the property to accommodate changes in the robot state while maintaining attraction to the original policy. As such, we investigate the use of primitives as a blending mechanism by considering that state deviations from the o
Externí odkaz:
http://arxiv.org/abs/2204.07026
One of the challenges of full autonomy is to have a robot capable of manipulating its current environment to achieve another environment configuration. This paper is a step towards this challenge, focusing on the visual understanding of the task. Our
Externí odkaz:
http://arxiv.org/abs/2003.06977
Off-policy ensemble reinforcement learning (RL) methods have demonstrated impressive results across a range of RL benchmark tasks. Recent works suggest that directly imitating experts' policies in a supervised manner before or during the course of tr
Externí odkaz:
http://arxiv.org/abs/2002.00149
Currently, usual approaches for fast robot control are largely reliant on solving online optimal control problems. Such methods are known to be computationally intensive and sensitive to model accuracy. On the other hand, animals plan complex motor a
Externí odkaz:
http://arxiv.org/abs/1912.03535
Highly dynamic tasks that require large accelerations and precise tracking usually rely on accurate models and/or high gain feedback. While kinematic optimization allows for efficient representation and online generation of hitting trajectories, lear
Externí odkaz:
http://arxiv.org/abs/1807.01918
Publikováno v:
In Neural Networks September 2020 129:109-122
Autor:
Sato, Kaiji, Maeda, Guilherme Jorge
Publikováno v:
In Precision Engineering 2009 33(2):175-186