Results 191 to 200 of about 117,918 (268)

Universal Gripper for Industrial Manipulation With Enhanced Rigid Mechanics and Self‐Adaptable Fingers

open access: yesAdvanced Robotics Research, EarlyView.
An enhanced universal gripper combining rigid mechanics with self‐adaptable fingers is presented for industrial automation. The novel six‐bar linkage with integrated compliant pad eliminates mechanical interference while enabling passive shape adaptation.
Muhammad Usman Khalid   +7 more
wiley   +1 more source

Efficient and Robust Standing Postures of Quadruped Robots

open access: yesAdvanced Robotics Research, EarlyView.
A calibrated static framework estimates load, optimizes torques, and adapts posture so quadruped robots stand efficiently and robustly under external payloads, achieving up to 50% lower torque demand. Inspired by the natural posture adjustments of animals under external loading, this article presents an optimization‐based framework for minimizing joint
Mohamad Kanaan   +5 more
wiley   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

open access: yesAdvanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang   +5 more
wiley   +1 more source

Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling

open access: yesAdvanced Robotics Research, EarlyView.
This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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