Results 201 to 210 of about 17,845,866 (289)

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Residual-Guided Hybrid Stochastic Modeling: A Two-Stage Learning Framework for Urban GNSS Positioning Enhancement. [PDF]

Sensors (Basel)
Yin J, Li W, Fan R, Yuan Y, Zhao Z, Xu D, Yang Z, Shen F.   +7 more
europepmc   +1 more source

Echinoderm‐Inspired Autonomy for Soft‐Legged Robots

Advanced Robotics Research, EarlyView.
Inspired by echinoderms, a modular soft robot achieves autonomous phototaxis without a central controller or explicit communication. Each limb independently adapts its actuation timing through local sensing and short‐term memory. Coordination emerges purely from physical interactions, demonstrating resilience to changes in morphology, environment, and ...
Harmannus A. H. Schomaker, Jelle de Vries, Johannes T. B. overvelde   +2 more
wiley   +1 more source

Letter to the editor: Autochthonous transmission patterns of dengue virus serotype 2 in Italy: evidence from outbreaks in 2024. [PDF]

Euro Surveill
Aguiar M, Pisaneschi G, Manfredi P, Landi A, Stollenwerk N.   +4 more
europepmc   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Integration of Reconfigurable p-Bit and 1R Crossbar Array for Memristive Probabilistic Computing. [PDF]

Adv Sci (Weinh)
Soh K, Kim JE, Chun SY, Hwang SI, Kim BS, Lee YJ, Jang HW, Yoon JH.   +7 more
europepmc   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

Uncertainty-aware electrification of university campuses: Matching demand with renewable generation for zero emissions.

Eng Sci Technol
Berna-Escriche C, Álvarez-Piñeiro L, Bastida-Molina P, Blanco-Muelas D.   +3 more
europepmc   +1 more source

The SATvac model of CD8+ T cell expansion and contraction phases considering memory and effector cell differentiation. [PDF]

PLoS Comput Biol
Seyyedizadeh SF, Christian DA, Adams TA.
europepmc   +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

Advanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano, Jianyu An, Dinesh Manocha, Huan Xu   +3 more
wiley   +1 more source