Results 81 to 90 of about 9,252,589 (289)
TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications
Advanced Robotics Research, EarlyView.TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince +3 more
wiley +1 more source
IEEE AccessCombined heat and power microgrids (CHPMGs) have become increasingly popular recently due to their ability to offer cost-effective and resilient solutions to support critical infrastructures.
Bo Hu +5 more
doaj +1 more source
Optimal Treatment Strategies for Critical Patients with Deep Reinforcement Learning
Personalized clinical decision support systems are increasingly being adopted due to the emergence of data-driven technologies, with this approach now gaining recognition in critical care.
Li, Lin +6 more
core +1 more source
Auditory–Tactile Congruence for Synthesis of Adaptive Pain Expressions in RoboPatients
Advanced Robotics Research, EarlyView.In this work, we explore auditory–tactile congruence for synthesizing adaptive vocal pain expressions in robopatients. Using a robopatient platform that integrates vocal pain sounds with palpation forces, we conducted 7680 trials across 20 participants.
Saitarun Nadipineni +4 more
wiley +1 more source
Alexandria Engineering JournalWith the rapid development of autonomous driving technology, issues regarding safe decision-making and multi-vehicle collaboration in complex urban environments have become increasingly prominent. To address the limitations of existing deep reinforcement
Zhongsheng Tang +3 more
doaj +1 more source
Partial Attention in Deep Reinforcement Learning for Safe Multi-Agent Control
CoRRAttention mechanisms excel at learning sequential patterns by discriminating data based on relevance and importance. This provides state-of-the-art performance in advanced generative artificial intelligence models. This paper applies this concept of an attention mechanism for multi-agent safe control.
Turki Bin Mohaya, Peter J. Seiler
openaire +2 more sources
Refined Risk Management in Safe Reinforcement Learning with a Distributional Safety Critic
, 2022 Safety is critical to broadening the real-world use of reinforcement learning (RL). Modeling the safety aspects using a safety-cost signal separate from the reward is becoming standard practice, since it avoids the problem of finding a good balance ...
Yang, Q. (author) +3 more
core
Advanced Robotics Research, EarlyView.Permanent magnet putty (PMP) integrates high‐coercivity NdFeB particles with a dynamic polyborosiloxane–Ecoflex matrix, achieving rapid self‐healing (90% mechanical recovery in 10 s) and magnetic recovery within 20 min. With twice the sensitivity of commercial putties, PMP enables precise 5–30 N force detection and discrimination between pressing and ...
Ruotong Zhao +5 more
wiley +1 more source
Frontiers in Energy ResearchIntroductionDynamic network reconfiguration is a critical tool for enhancing the operational efficiency and security of power distribution networks. However, traditional model-based optimization methods are often computationally intensive and rely on ...
Ke Li +7 more
doaj +1 more source
Learning Strict Nash Equilibria through Reinforcement [PDF]
This paper studies the analytical properties of the reinforcement learning model proposed in Erev and Roth (1998), also termed cumulative reinforcement learning in Laslier et al (2001).
Ianni, Antonella
core