Results 101 to 110 of about 8,579,021 (292)
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
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
Robust Solutions of Optimization Problems Affected by Uncertain Probabilities [PDF]
In this paper we focus on robust linear optimization problems with uncertainty regions defined by ø-divergences (for example, chi-squared, Hellinger, Kullback-Leibler).
De Waegenaere, A.M.B. +4 more
core
Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion
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
Existence of a solution and variational principles for vector equilibrium problems
In this paper, we prove an existence result for a solution to the vector equilibrium problems. Then, we establish variational principles, that is, vector optimization formulations of set-valued maps for vector equilibrium problems.
Ansari Q., Yao J., Konnov I.
core
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
Efficient and Robust Standing Postures of Quadruped Robots
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
Efficiency of coordinate descent methods on huge-scale optimization problems [PDF]
In this paper we propose new methods for solving huge-scale optimization problems. For problems of this size, even the simplest full-dimensional vector operations are very expensive.
NESTEROV, Yurii
core
Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling
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
Sharp Efficiency for Vector Equilibrium Problems on Banach Spaces
The concept of sharp efficient solution for vector equilibrium problems on Banach spaces is proposed. Moreover, the Fermat rules for local efficient solutions of vector equilibrium problems are extended to the sharp efficient solutions by means of the ...
Si-Huan Li +3 more
doaj +1 more source

