Results 141 to 150 of about 116,019 (342)

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck   +4 more
wiley   +1 more source

Degeneracy Sensing Light Detection and Ranging‐Inertial Simultaneous Localization and Mapping with Dual‐Layer Resistant Odometry and Scan‐Context Loop‐Closure Detection Backend in Diverse Environments

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper presents a degeneracy‐aware light detection and ranging (LiDAR)‐inertial framework that enhances LiDAR simultaneous localization and mapping performance in challenging environments. The proposed system integrates a dual‐layer robust odometry frontend with a Scan‐Context‐based loop‐closure detection backend.
Haoming Yang   +4 more
wiley   +1 more source

Applications of a saving method with max-min ant system to a vehicle routing problem with time windows and speed limits

open access: yesKKU Engineering Journal, 2014
This study aims to solve a Vehicle Routing Problem with Time Windows and Speed Limits (VRPTWSL), which has received considerable attention in recent years.
Suphan Sodsoon   +2 more
doaj  

Multimodal Locomotion of Soft Robots

open access: yesAdvanced Intelligent Systems, EarlyView.
This review comprehensively surveys recent advances in multimodal locomotion within soft robotics. Typical locomotion modes are summarized and categorized. Furthermore, the underlying mechanisms enabling multimodal locomotion are discussed and classified into three primary categories: active control‐based, reconfiguration‐based, and environment ...
Zihao Yuan   +4 more
wiley   +1 more source

Bio‐to‐Robot Transfer of Fish Sensorimotor Dynamics via Interpretable Model

open access: yesAdvanced Intelligent Systems, EarlyView.
This study demonstrates how a biologically interpretable model trained on real‐fish muscle activity can accurately predict the motion of a robotic fish. By linking real‐fish sensorimotor dynamics with robotic fish, the work offers a transparent, data‐efficient framework for transferring biological intelligence to bioinspired robotic systems.
Waqar Hussain Afridi   +6 more
wiley   +1 more source

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