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Robot autonomous gras** and assembly skill learning based on deep reinforcement learning
This paper proposes a deep reinforcement learning-based framework for robot autonomous gras** and assembly skill learning. Meanwhile, a deep...
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Simultaneously learning intentions and preferences during physical human-robot cooperation
The advent of collaborative robots allows humans and robots to cooperate in a direct and physical way. While this leads to amazing new opportunities...
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State-Dependent Maximum Entropy Reinforcement Learning for Robot Long-Horizon Task Learning
Task-oriented robot learning has shown significant potential with the development of Reinforcement Learning (RL) algorithms. However, the learning of...
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Learning Robust Locomotion for Bipedal Robot via Embedded Mechanics Properties
Reinforcement learning (RL) provides much potential for locomotion of legged robot. Due to the gap between simulation and the real world, achieving...
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A Reinforcement Learning Approach for Continuum Robot Control
Rigid joint manipulators are limited in their movement and degrees of freedom (DOF), while continuum robots possess a continuous backbone that allows...
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Learning curve for robot-assisted knee arthroplasty; optimizing the learning curve to improve efficiency
The introduction of robot-assisted (RA) systems in knee arthroplasty has challenged surgeons to adopt the new technology in their customized surgical...
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NAO Robot Learns to Interact with Humans through Imitation Learning from Video Observation
One option for teaching a robot new skills is to use learning from demonstration techniques. While traditional techniques often involve expensive...
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Crowd-Aware Socially Compliant Robot Navigation via Deep Reinforcement Learning
Navigating in crowd environments is challenging for mobile robots because not only the safety but also the comfort of surrounding pedestrians must be...
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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning
The overall performance of multi-robot collaborative systems is significantly affected by the multi-robot task allocation. To improve the...
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On robot grasp learning using equivariant models
Real-world grasp detection is challenging due to the stochasticity in grasp dynamics and the noise in hardware. Ideally, the system would adapt to...
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Machine learning enabled robot-assisted virtual health monitoring system design and development
The robot-based approach aims to address the challenge of providing timely medical assistance to individuals who cannot commit to extended...
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A Review on the Effectiveness of Machine Learning and Deep Learning Algorithms for Collaborative Robot
More and more, we may expect to see robots working side by side with humans as technology advances. Collaborative robot (cobot) is a methodology that...
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Learning modular language-conditioned robot policies through attention
Training language-conditioned policies is typically time-consuming and resource-intensive. Additionally, the resulting controllers are tailored to...
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Intelligent learning model-based skill learning and strategy optimization in robot grinding and polishing
With the rapid advancement of manufacturing in China, robot machining technology has become a popular research subject. An increasing number of...
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Exploration-based model learning with self-attention for risk-sensitive robot control
Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for...
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Gaussian-process-based robot learning from demonstration
Learning from demonstration allows to encode task constraints from observing the motion executed by a human teacher. We present a...
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Dynamic warning zone and a short-distance goal for autonomous robot navigation using deep reinforcement learning
Robot navigation in crowded environments has recently benefited from advances in deep reinforcement learning (DRL) approaches. However, it still...
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A Robot Learning from Demonstration Method Based on Neural Network and Teleoperation
Industrial robots are widely employed in electronics, aerospace, machining, and other fields due to their flexibility, efficiency, and accuracy...
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Study on force control for robot massage with a model-based reinforcement learning algorithm
When a robot end-effector contacts human skin, it is difficult to adjust the contact force autonomously in an unknown environment. Therefore, a robot...
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Robot Subgoal-guided Navigation in Dynamic Crowded Environments with Hierarchical Deep Reinforcement Learning
Although deep reinforcement learning has recently achieved some successes in robot navigation, there are still unsolved problems. Particularly, a...