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   Articles with "sim real" as a keyword



Sim-to-real pipeline for training autonomous obstacle avoidance of underwater robots based on high-fidelity model

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recommendations! Published in 2025 at "Robotica"

DOI: 10.1017/s0263574725101999

Abstract: Abstract Underwater robots conducting inspections require autonomous obstacle avoidance capabilities to ensure safe operations. Training methods based on reinforcement learning (RL) can effectively develop autonomous obstacle avoidance strategies for underwater robots; however, training in real… read more here.

Keywords: sim real; autonomous obstacle; underwater robots; obstacle ... See more keywords

A Sim-to-Real Pipeline for Deep Reinforcement Learning for Autonomous Robot Navigation in Cluttered Rough Terrain

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recommendations! Published in 2021 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2021.3093551

Abstract: Robots that autonomously navigate real-world 3D cluttered environments need to safely traverse terrain with abrupt changes in surface normals and elevations. In this letter, we present the development of a novel sim-to-real pipeline for a… read more here.

Keywords: pipeline; sim real; robot; terrain ... See more keywords

Sim-to-Real Surgical Robot Learning and Autonomous Planning for Internal Tissue Points Manipulation Using Reinforcement Learning

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recommendations! Published in 2023 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2023.3254860

Abstract: Indirect simultaneous positioning (ISP), where internal tissue points are placed at desired locations indirectly through the manipulation of boundary points, is a type of subtask frequently performed in robotic surgeries. Although challenging due to complex… read more here.

Keywords: reinforcement learning; internal tissue; manipulation; sim real ... See more keywords

In-Hand Object Classification and Pose Estimation With Sim-to-Real Tactile Transfer for Robotic Manipulation

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recommendations! Published in 2024 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2023.3334971

Abstract: Dexterous robotic grasping gains great benefits from tactile sensation, but delicate object exploration by tactile information is challenged by difficulty in rich and efficient data production. In this letter, we propose a tactile-based in-hand object… read more here.

Keywords: classification; sim real; object classification; hand object ... See more keywords

FPGA-Accelerated Sim-to-Real Control Policy Learning for Robotic Arms

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems II: Express Briefs"

DOI: 10.1109/tcsii.2024.3353690

Abstract: Sim-to-real robot learning has been used in various applications, but its implementation in software may not provide the best performance. This tutorial describes how hardware acceleration based on Field-Programmable Gate Array (FPGA) technology for deep… read more here.

Keywords: control; sim real; robotic arms; policy learning ... See more keywords

Reinforcement Learning and Sim-to-Real Transfer of Reorientation and Landing Control for Quadruped Robots on Asteroids

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recommendations! Published in 2024 at "IEEE Transactions on Industrial Electronics"

DOI: 10.1109/tie.2024.3360604

Abstract: In surface exploration missions, wheeled planetary vehicles have difficulty traveling on asteroids due to their weak gravitational fields. With the rapid development of hardware performance and control methods, quadruped robots have great potential to serve… read more here.

Keywords: control; sim real; real transfer; quadruped robots ... See more keywords

Effective Learning Mechanism Based on Reward-Oriented Hierarchies for Sim-to-Real Adaption in Autonomous Driving Systems

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recommendations! Published in 2025 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2024.3524882

Abstract: Autonomous vehicles in Intelligent Transportation Systems aim to boost the adaptability performances of complex problem-solving behaviour in the Sim-to-Real self-driving mission. However, the difficulty for Sim2Real adaption is the so-called “catastrophic forgetting” challenge, i.e., the… read more here.

Keywords: sim real; adaption; reward oriented; autonomous driving ... See more keywords

AAV Swarm Cooperative Search Based on Scalable Multiagent Deep Reinforcement Learning With Digital Twin-Enabled Sim-to-Real Transfer

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recommendations! Published in 2025 at "IEEE Transactions on Mobile Computing"

DOI: 10.1109/tmc.2025.3530438

Abstract: Cooperative target search (CTS) technology is highly desirable in various multi-autonomous aerial vehicle (AAV) applications. However, searching for unknown targets in a dynamic threatening environment is a challenging problem, especially for AAVs with limited sensing… read more here.

Keywords: aav swarm; search; sim real; twin enabled ... See more keywords

Unsupervised Sim-to-Real Adaptation for Environmental Recognition in Assistive Walking

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recommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"

DOI: 10.1109/tnsre.2022.3176410

Abstract: Powered lower-limb prostheses with vision sensors are expected to restore amputees’ mobility in various environments with supervised learning-based environmental recognition. Due to the sim-to-real gap, such as real-world unstructured terrains and the perspective and performance… read more here.

Keywords: adaptation; environmental recognition; sim real; real world ... See more keywords

From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers

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recommendations! Published in 2024 at "IEEE Transactions on Robotics"

DOI: 10.1109/tro.2024.3463407

Abstract: Designing and validating controllers for connected and automated vehicles to enhance traffic flow presents significant challenges, from the complexity of replicating real-world stop-and-go traffic dynamics in simulation, to the intricacies involved in transitioning from simulation… read more here.

Keywords: sim real; training; controller; pipeline ... See more keywords

Deep Reinforcement Learning for Sim-to-Real Robot Navigation with a Minimal Sensor Suite for Beach-Cleaning Applications

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recommendations! Published in 2025 at "Applied Sciences"

DOI: 10.3390/app151910719

Abstract: Autonomous beach-cleaning robots require reliable, low-cost navigation on sand. We study Sim-to-Real transfer of deep reinforcement learning (DRL) policies using a minimal sensor suite—wheel-encoder odometry and a single 2-D LiDAR—on a 30 kg differential-drive platform… read more here.

Keywords: navigation; sim real; reinforcement learning; deep reinforcement ... See more keywords