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1
Interface Based on Electrooculography for Velocity Control of a Robot Arm
Published 2010-01-01“…In this paper, the experimental results obtained with a real robot arm are shown.…”
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2
Neural network-based robot localization using visual features
Published 2024-10-01“…The experiments were conducted using both simulation and a real robot. The Webots environment with the virtual humanoid robot NAO was used for the simulations. …”
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3
Intentionally-underestimated value function at terminal state for temporal-difference learning with mis-designed reward
Published 2025-03-01“…Simulation results showed that the proposed method improves the success rate for 24 tasks with different reward designs from 10/24 in the conventional method to 20/24. Real-robot experiments also demonstrated that the proposed method enables to learn the optimal policy even in the case that the conventional method fails.…”
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4
Dynamics Model Abstraction Scheme Using Radial Basis Functions
Published 2012-01-01“…Experiments are done using a real robot’s arm, and trajectory data are gathered during various trials manipulating different objects. …”
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5
Segment, Compare, and Learn: Creating Movement Libraries of Complex Task for Learning from Demonstration
Published 2025-01-01“…Its effectiveness has been validated in manipulation tasks with a real robot, as well as through comparisons with state-of-the-art algorithms.…”
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6
Flexible Model Predictive Control for Bounded Gait Generation in Humanoid Robots
Published 2025-01-01“…In addition, the validation of the simulation of real robot motion on the robots CASBOT and Openloong, in turn, demonstrates the effectiveness and robustness of our approach.…”
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7
Repetitive Control of Robotic Joint With Variable Impedance Utilizing Agonist-Antagonist Muscle Pair Structure Based on Virtual Trajectories
Published 2025-01-01“…In this study, the repetitive control based on virtual trajectory, which is a model-free control method proposed for flexible human multi-joints, is extended and applied to a real robotic joint with a variable mechanical impedance mechanism. …”
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8
Rapid learning with phase-change memory-based in-memory computing through learning-to-learn
Published 2025-02-01“…We demonstrate the versatility of our approach in two scenarios: a convolutional neural network performing image classification and a biologically-inspired spiking neural network generating motor commands for a real robotic arm. Both models rapidly learn with few parameter updates. …”
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Dynamic Task Planning for Multi-Arm Harvesting Robots Under Multiple Constraints Using Deep Reinforcement Learning
Published 2025-01-01“…We will research improving the positioning accuracy of fruits in the future, which will make it possible to apply this framework to real robots.…”
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