Results 181 to 190 of about 1,052,376 (334)

Modulus‐Switchable Miniature Robots for Biomedical Applications: A Review

Advanced Robotics Research, EarlyView.
Materials, robot designs, proof‐of‐concept functions, and biomedical applications of modulus‐switchable miniature robots. Miniature soft robots have shown great potential in biomedical applications due to their excellent controllability and suitable mechanical properties in biological environments.
Chunyun Wei, Yibin Wang, Jiangfan Yu
wiley   +1 more source

Deep multi-agent reinforcement learning

, 2018
A plethora of real world problems, such as the control of autonomous vehicles and drones, packet delivery, and many others consists of a number of agents that need to take actions based on local observations and can thus be formulated in the multi-agent ...
Jakob N Foerster, Foerster, Jakob N
core   +1 more source

Soft Robotic Snake with Tunable Undulatory Gait for Efficient Underwater Locomotion

Advanced Robotics Research, EarlyView.
This study designs an underwater soft snake robot using 3D‐printed soft actuators, controlled by specific signals to generate sinusoidal undulation. Results show a positive correlation between speed and swing amplitude, with optimal performance at 2/3π phase offset, PLA tail, 1.2 voltage growth rate, and 6s undulation period achieving a maximum speed ...
Huichen Ma, Junjie Zhou, Raye Yeow
wiley   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Developing A Deep Reinforcement Learning Model for Safety Risk Prediction at Subway Construction Sites

Underground construction work is heavily affected by surrounding hydrogeology, adjacent pipelines, and existing subway lines, which can lead to a high degree of uncertainty and generate safety risk on site.
Zhou, Zhipeng, Luan, Haiying, Lin, Dong, Zhuo, Wen, Cui, Jianqiang, Chen, Yudi   +5 more
core   +1 more source

Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation [PDF]

, 2018
Deep reinforcement learning (RL) has shown impressive results in a variety of domains, learning directly from high-dimensional sensory streams. However, when neural networks are trained in a fixed environment, such as a single level in a video game, they
Bontrager, Philip, Khalifa, Ahmed, NeurIPS Deep RL Workshop 2018, Torrado, Ruben Rodriguez, Risi, Sebastian, Rodriguez Torrado, Ruben, Justesen, Niels, Togelius, Julian   +7 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

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

A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics

Advanced Robotics Research, EarlyView.
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett, Maxwell Hammond, Niloufar Seyfi, Amirreza Fahim Golestaneh, Venanzio Cichella, Caterina Lamuta   +5 more
wiley   +1 more source

Verifiable reinforcement learning via policy extraction

, 2019
© 2018 Curran Associates Inc.All rights reserved. While deep reinforcement learning has successfully solved many challenging control tasks, its real-world applicability has been limited by the inability to ensure the safety of learned policies.
Bastani, Osbert, Pu, Yewen, Solar Lezama, Armando   +2 more
core