Results 111 to 120 of about 314,651 (266)

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

Reinforcement Learning Algorithms for Online Single-Machine Scheduling [PDF]

open access: yesAnnals of computer science and information systems, 2020
Yuanyuan Li   +4 more
doaj   +1 more source

Beyond Efficiency: Emotion-Aware Competitive Analysis of Online Algorithms

open access: yesIEEE Access
Many of today’s infrastructures, from transportation and healthcare to cloud computing and digital marketplaces, rely on algorithms that must act online, meaning they make decisions sequentially without knowledge of the future.
Christine Markarian
doaj   +1 more source

Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion

open access: yesAdvanced Robotics Research, EarlyView.
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza   +3 more
wiley   +1 more source

Online Algorithms for Warehouse Management.

open access: yes, 2019
As the prevalence of E-commerce continues to grow, the efficient operation of warehouses and fulfillment centers is becoming increasingly important. To this end, many such warehouses are adding automation in order to help streamline operations, drive down costs, and increase overall efficiency.
Philip Dasler, David M. Mount
openaire   +3 more sources

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

open access: yesAdvanced Robotics Research, EarlyView.
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka   +3 more
wiley   +1 more source

A Multidirectional Textile Interface for Remote Control Using Dynamic Area‐Based Capacitance Modulation

open access: yesAdvanced Robotics Research, EarlyView.
Here, we present a textile, wearable capacitive interface enabling multidirectional remote control by dynamically modulating electrode overlap and spacing via a freely gliding upper electrode. A forearm‐mounted prototype drives robotic and media tasks with 12–15 ms latency, maintains < 0.8% drift after 500 cycles, and remains stably functional at 90 ...
Cagatay Gumus   +8 more
wiley   +1 more source

A Soft Robotic Fish With a Dielectric Elastomer Actuator Body and Negative Stiffness Spine

open access: yesAdvanced Robotics Research, EarlyView.
This work introduces a bio‐mimetic soft robotic fish driven by fiber‐reinforced dielectric elastomer actuators integrated as its body. By prestretching this active skin against a flexible spine, a negative stiffness system is created, enabling large‐amplitude bending.
Markus Koenigsdorff   +4 more
wiley   +1 more source

Online Algorithms with Unreliable Guidance

open access: yesCoRR
This paper introduces a new model for ML-augmented online decision making, called online algorithms with unreliable guidance (OAG). This model completely separates between the predictive and algorithmic components, thus offering a single well-defined analysis framework that relies solely on the considered problem. Formulated through the lens of request-
Julien Dallot   +4 more
openaire   +2 more sources

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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