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
Overcoming Data Scarcity in Roadside Thermal Imagery: A New Dataset and Weakly Supervised Incremental Learning Framework. [PDF]
Sensors (Basel)Pettirsch A, Garcia-Hernandez A.
europepmc +1 more source
An integrated classification model for incremental learning. [PDF]
Multimed Tools Appl, 2021 Hu J +7 more
europepmc +1 more source
An AI‐Enabled All‐In‐One Visual, Proximity, and Tactile Perception Multimodal Sensor
Advanced Robotics Research, EarlyView.Targeting integrated multimodal perception of robots, an AI‐enabled all‐in‐one multimodal sensor is proposed. This sensor is capable of perceiving three types of modalities, including vision, proximity, and tactility. By toggling an ultraviolet light and adjusting the camera focus, it switches smoothly between multiple perceptual modalities, enabling ...
Menghao Pu +7 more
wiley +1 more source
Generative Diffusion-Based Task Incremental Learning Method for Decoding Motor Imagery EEG. [PDF]
Brain SciYang Y, Li M, Liu J.
europepmc +1 more source
Combining BERT Model with Semi-Supervised Incremental Learning for Heterogeneous Knowledge Fusion of High-Speed Railway On-Board System. [PDF]
Comput Intell Neurosci, 2022 Zhou LJ, Zhao ZP, Dang JW.
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Mobilising Land Value Increments for Urban Development: Learning from the Latin America Experience [PDF]
, 2002 Martin Smolka, Fernanda Furtado
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Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Exploring multi-granularity balance strategy for class incremental learning via three-way granular computing. [PDF]
Brain InformXian Y, Yu H, Wang Y, Wang G.
europepmc +1 more source
GBM-ILM: Grey-Box Modeling Based on Incremental Learning and Mechanism for Unmanned Surface Vehicles [PDF]
Mengwei Zhang +3 more
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