Results 71 to 80 of about 38,367 (259)

Online Hyperparameter Tuning in Bayesian Optimization for Material Parameter Identification: An Application in Strain-Hardening Plasticity for Automotive Structural Steel

open access: yesAppliedMath
Effective identification of strain-hardening parameters is essential for predictive plasticity models used in automotive applications. However, the performance of Bayesian optimization depends strongly on kernel hyperparameters in the Gaussian-process ...
Teng Long   +3 more
doaj   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

open access: yesAdvanced 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   +5 more
wiley   +1 more source

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

open access: yesAdvanced 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

A Combinatorial Approach to Hyperparameter Optimization

open access: yesProceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI
Published ...
Krishna Khadka   +4 more
openaire   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

open access: yesAdvanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Hyperparameter Optimization

open access: yesThe Journal of The Institute of Image Information and Television Engineers, 2023
Marc Becker   +2 more
openaire   +2 more sources

A comparative analysis of hyperparameter optimization using LSTM-based deep learning models for urban air quality predictions

open access: yesAin Shams Engineering Journal
Air pollution poses significant threats to human health and the environment, necessitating accurate prediction models for effective management and mitigation strategies.
Beytullah Eren   +3 more
doaj   +1 more source

Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot

open access: yesAdvanced Robotics Research, EarlyView.
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini   +7 more
wiley   +1 more source

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

open access: yesAdvanced 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   +8 more
wiley   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao   +4 more
wiley   +1 more source

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