Results 141 to 150 of about 18,707 (285)

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

Advanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao, Yinzhao Dong, Ji Ma, Peng Lu   +3 more
wiley   +1 more source

Rough Statistical Convergence of Double Sequences in Probabilistic Normed Spaces

Communications in Mathematics and Applications
In this paper, we have defined rough convergence and rough statistical convergence of double sequences in probabilistic normed spaces which is more generalized version than the rough statistical convergence of double sequences in normed linear spaces. Also, we have defined rough statistical cluster points of double sequences and then, investigated some
Rahul Mondal, Nesar Hossain
openaire   +2 more sources

Certain Aspects of Deferred Statistical Convergence of Sequences in Probabilistic Normed Spaces

In this research article, we have primarily focused on the circumstantial investigation of deferred statistical convergence of sequences and investigated some fundamental results compatible with the structure of a probabilistic normed space. Additionally,
Hossain, Nesar, Mondal, Rahul
core  

Information Transmission Strategies for Self‐Organized Robotic Aggregation

Advanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng, Zihan Li, Yifeng Shao, Jinhao Liu, Li Yu, Shuguang Li   +5 more
wiley   +1 more source

Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control

Machine Learning with Applications
Discrete reinforcement learning (RL) offers interpretability advantages compared to continuous reinforcement learning. Neural networks used in continuous RL behave like black boxes that do not show an obvious relationship between the system states and ...
Alberto Gil-Maciá, J. Enrique Sierra-García, Matilde Santos   +2 more
doaj   +1 more source

Multimodal Actuation and Environment Adaptive Strategies of Bio‐Inspired Micro/Nanorobots in Precision Medicine

Advanced Robotics Research, EarlyView.
An introduction for multidrive and environment‐adaptive micro/nanorobotics: design and fabrication strategies, intelligent actuation, and their applications. Various intelligent actuation approaches—magnetic, acoustic, optical, chemical, and biological—can be synergistically designed to enhance flexibility and adaptive behavior for precision medicine ...
Aiqing Ma, Han Gong, Jiacheng Ouyang, Liqi Chen, Tianfang Kang, Yiran He, Guojun Huang, Sidi Zheng, Ting Yin, Hong Pan, Lintao Cai   +10 more
wiley   +1 more source

Unawareness, Beliefs and Games [PDF]

We define a generalized state-space model with interactive unawareness and probabilistic beliefs. Such models are desirable for many potential applications of asymmetric unawareness.
Heifetz, Aviad, Meier, Martin, Schipper, Burkhard C.   +2 more
core   +2 more sources

Cloud drift optimization algorithm as a nature-inspired metaheuristic

Discover Computing
This study introduces the Cloud Drift Optimization (CDO) algorithm, an innovative nature-inspired metaheuristic approach to solving complex optimization problems.
Mohammad Alibabaei Shahraki
doaj   +1 more source

The target projection dynamic [PDF]

This paper studies the target projection dynamic, which is a model of myopic adjustment for population games. We put it into the standard microeconomic framework of utility maximization with control costs.
Voorneveld, Mark, Tsakas, Elias
core  

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source