Results 81 to 90 of about 98,895 (273)

Classifying Options for Deep Reinforcement Learning

, 2016
In this paper we combine one method for hierarchical reinforcement learning - the options framework - with deep Q-networks (DQNs) through the use of different "option heads" on the policy network, and a supervisory network for choosing between the ...
Arulkumaran, Kai, Bharath, Anil Anthony, Dilokthanakul, Nat, Shanahan, Murray   +3 more
core  

3D Printing of Stretchable, Compressible and Conductive Porous Polyurethane for Soft Robotics

Advanced Materials Technologies, EarlyView.
A 3D‐printable porous dopamine‐polyurethane acrylate elastomer results in conductive, stretchable, and compressible structures that can be metallized in situ through catechol‐mediated silver reduction. The resulting material function as both compliant soft robot with a and strain sensors without complex assemblies, enabling fully 3D‐printed soft ...
Ouriel Bliah, Konstantin Sakharov, Pooi See Lee, Shlomo Magdassi   +3 more
wiley   +1 more source

Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

Advanced Robotics Research, EarlyView.
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang, Zhipeng Jiang, Sun Hwa Kwon, Matthew Ibrahim, Alexander Dang, Lin Dong   +5 more
wiley   +1 more source

Learning to Learn: Hierarchical Meta-Critic Networks

IEEE Access, 2019
In recent years, deep reinforcement learning methods have achieved impressive performance in many different fields, including playing games, robotics, and dialogue systems.
Zhixiong Xu, Lei Cao, Xiliang Chen
doaj   +1 more source

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

Multi‐Material Additive Manufacturing of Soft Robotic Systems: A Comprehensive Review

Advanced Robotics Research, EarlyView.
This review explores the transformative role of multi‐material additive manufacturing (MMAM) in the development of soft robotic systems. It presents current techniques, materials, and design strategies that enable functionally graded and adaptive structures.
Ritik Raj, Quan‐Chen Song, Jia‐Yang Juang   +2 more
wiley   +1 more source

Crossmodal Attentive Skill Learner

, 2018
This paper presents the Crossmodal Attentive Skill Learner (CASL), integrated with the recently-introduced Asynchronous Advantage Option-Critic (A2OC) architecture [Harb et al., 2017] to enable hierarchical reinforcement learning across multiple sensory ...
How, Jonathan P., Kim, Dong-Ki, Omidshafiei, Shayegan, Pazis, Jason   +3 more
core  

Hard‐Magnetic Soft Millirobots in Underactuated Systems

Advanced Robotics Research, EarlyView.
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang, Zixuan Zhang, Bingyan Li, Junkai Wang, Hongcheng Gu   +4 more
wiley   +1 more source

Hierarchical Intermittent Motor Control With Deterministic Policy Gradient

IEEE Access, 2019
It has been evidenced that the neural motor control exploits the hierarchical and intermittent representation. In this paper, we propose a hierarchical deep reinforcement learning (DRL) method to learn the continuous control policy across multiple levels,
Haibo Shi, Yaoru Sun, Guangyuan Li, Fang Wang, Daming Wang, Jie Li   +5 more
doaj   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source