English
Related papers

Related papers: Machine Learning for Robotic Manipulation

200 papers

Traditional machine learning mainly supervised learning, follows the assumptions of closed-world learning, i.e., for each testing class, a training class is available. However, such machine learning models fail to identify the classes which…

Machine Learning · Computer Science 2022-02-22 Jitendra Parmar , Satyendra Singh Chouhan , Vaskar Raychoudhury , Santosh Singh Rathore

Reinforcement learning (RL), particularly its combination with deep neural networks referred to as deep RL (DRL), has shown tremendous promise across a wide range of applications, suggesting its potential for enabling the development of…

Robotics · Computer Science 2024-09-17 Chen Tang , Ben Abbatematteo , Jiaheng Hu , Rohan Chandra , Roberto Martín-Martín , Peter Stone

Humanoid robots hold great potential to perform various human-level skills, involving unified locomotion and manipulation in real-world settings. Driven by advances in machine learning and the strength of existing model-based approaches,…

Machine learning develops rapidly, which has made many theoretical breakthroughs and is widely applied in various fields. Optimization, as an important part of machine learning, has attracted much attention of researchers. With the…

Machine Learning · Computer Science 2019-10-24 Shiliang Sun , Zehui Cao , Han Zhu , Jing Zhao

Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning…

Machine Learning and Inference methods have become ubiquitous in our attempt to induce more abstract representations of natural language text, visual scenes, and other messy, naturally occurring data, and support decisions that depend on…

Machine Learning · Computer Science 2020-05-27 Dan Roth

The newly emerged machine learning (e.g. deep learning) methods have become a strong driving force to revolutionize a wide range of industries, such as smart healthcare, financial technology, and surveillance systems. Meanwhile, privacy has…

Machine Learning · Computer Science 2020-11-25 Bo Liu , Ming Ding , Sina Shaham , Wenny Rahayu , Farhad Farokhi , Zihuai Lin

The arrival of Machine Learning (ML) completely changed how we can unlock valuable information from data. Traditional methods, where everything was stored in one place, had big problems with keeping information private, handling large…

Big data and machine learning are driving comprehensive economic and social transformations and are rapidly re-shaping the toolbox and the methodologies of applied scientists. Machine learning tools are designed to learn functions from data…

Fluid Dynamics · Physics 2024-04-16 M. A. Mendez , J. Dominique , M. Fiore , F. Pino , P. Sperotto , J. Van den Berghe

The demand for artificial intelligence has grown significantly over the last decade and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, in order to increase…

Machine Learning · Computer Science 2022-11-28 Joost Verbraeken , Matthijs Wolting , Jonathan Katzy , Jeroen Kloppenburg , Tim Verbelen , Jan S. Rellermeyer

Robots are expected to replace menial tasks such as housework. Some of these tasks include nonprehensile manipulation performed without grasping objects. Nonprehensile manipulation is very difficult because it requires considering the…

Robotics · Computer Science 2022-06-23 Yuki Saigusa , Sho Sakaino , Toshiaki Tsuji

With great progress in the development of Generative Adversarial Networks (GANs), in recent years, the quest for insights in understanding and manipulating the latent space of GAN has gained more and more attention due to its wide range of…

Machine Learning · Computer Science 2021-02-25 Toan Pham Van , Tam Minh Nguyen , Ngoc N. Tran , Hoai Viet Nguyen , Linh Bao Doan , Huy Quang Dao , Thanh Ta Minh

The ongoing deep learning revolution has allowed computers to outclass humans in various games and perceive features imperceptible to humans during classification tasks. Current machine learning techniques have clearly distinguished…

Robotics · Computer Science 2023-06-07 Joshua Paul Powers

Machine learning has found its way into almost every area of science and engineering, and we are only at the beginning of its exploration across fields. Being a popular, versatile and powerful framework, machine learning has proven most…

Computational Engineering, Finance, and Science · Computer Science 2022-03-15 Siddhant Kumar , Dennis M. Kochmann

Over the past decade, deep neural networks have demonstrated significant success using the training scheme that involves mini-batch stochastic gradient descent on extensive datasets. Expanding upon this accomplishment, there has been a…

Machine Learning · Computer Science 2024-11-11 Jaehyeon Son , Soochan Lee , Gunhee Kim

Dexterous manipulation is a crucial yet highly complex challenge in humanoid robotics, demanding precise, adaptable, and sample-efficient learning methods. As humanoid robots are usually designed to operate in human-centric environments and…

Robotics · Computer Science 2026-02-26 Edgar Welte , Rania Rayyes

Deep learning has recently become one of the most popular sub-fields of machine learning owing to its distributed data representation with multiple levels of abstraction. A diverse range of deep learning algorithms are being employed to…

Computer Vision and Pattern Recognition · Computer Science 2018-04-12 Rajat Kumar Sinha , Ruchi Pandey , Rohan Pattnaik

There is no denying the tremendous leap in the performance of machine learning methods in the past half-decade. Some might even say that specific sub-fields in pattern recognition, such as machine-vision, are as good as solved, reaching…

Machine Learning · Computer Science 2018-02-15 Amir Rosenfeld , John K. Tsotsos

In recent years, machine learning (ML) has become a key enabling technology for the sciences and industry. Especially through improvements in methodology, the availability of large databases and increased computational power, today's ML…

Artificial Intelligence · Computer Science 2019-09-27 Wojciech Samek , Klaus-Robert Müller

Automated analyses of the outcome of a simulation have been an important part of atomistic modeling since the early days, addressing the need of linking the behavior of individual atoms and the collective properties that are usually the…

Chemical Physics · Physics 2019-05-22 Michele Ceriotti