Tianle Huang - IEEE Xplore Author Profile

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Author details

Tianle Huang

Publications

2

Citations

6

Publications by Year

20232024

Co-Authors:

Hosik ChaeIrfan EssaSehoon HaSehoon HalDennis W. Hong

Show All Co-Authors (9)

Tianle Huang

Affiliation

Georgia Institute of Technology, GA, USA

Publication Topics

Deep Reinforcement Learning,
Domain Adaptation,
Interesting Direction For Future Research,
Legged Robots,
Markov Decision Process,
Policy Learning,
Reward Function,
System Identification,
Vanilla,
Baseline Algorithms,
Bayesian Optimization,
Buoyancy

Publications

2

Citations

6

Publications by Year

20232024

Co-Authors:

Hosik Chae
Irfan Essa
Sehoon Ha
Sehoon Hal
Dennis W. Hong

Show All Co-Authors (9)

Author's Published Works

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Showing 1-2 of 2 results

Conferences (2)

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Dennis W. Hong(2)
Tianle Huang(2)
Nitish Sontakke(2)
Sehoon Hal(1)
K. Niranjan Kumar(1)
Georgia Institute of Technology, GA, USA(1)
University of Southern California, Los Angeles, CA, USA(1)
University of California, Los Angeles, CA, USA(1)
Department of Computer Science, Los Angeles (UCLA), University of California, Los Angeles, CA, USA(1)
School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA(1)
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(1)
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(1)
IEEE(2)
Media(1)
Abu Dhabi, United Arab Emirates(1)
Detroit, MI, USA(1)
Deep Reinforcement Learning(2)
Domain Adaptation(2)
Interesting Direction For Future Research(2)
Legged Robots(2)
Markov Decision Process(2)

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BayRnTune: Adaptive Bayesian Domain Randomization via Strategic Fine-tuning

Tianle Huang;Nitish Sontakke;K. Niranjan Kumar;Irfan Essa;Stefanos Nikolaidis;Dennis W. Hong;Sehoon Ha

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2024 | Conference Paper |

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Domain randomization (DR), which entails training a policy with randomized dynamics, has proven to be a simple yet effective algorithm for reducing the gap between simulation and the real world. However, DR often requires careful tuning of randomization parameters. Methods like Bayesian Domain Randomization (Bayesian DR) and Active Domain Randomization (Adaptive DR) address this issue by automatin...Show More

BayRnTune: Adaptive Bayesian Domain Randomization via Strategic Fine-tuning

Tianle Huang;Nitish Sontakke;K. Niranjan Kumar;Irfan Essa;Stefanos Nikolaidis;Dennis W. Hong;Sehoon Ha

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2024 | Conference Paper |

Residual Physics Learning and System Identification for Sim-to-real Transfer of Policies on Buoyancy Assisted Legged Robots

Nitish Sontakke;Hosik Chae;Sangjoon Lee;Tianle Huang;Dennis W. Hong;Sehoon Hal

2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2023 | Conference Paper |

Cited by: Papers (6)

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The light and soft characteristics of Buoyancy Assisted Lightweight Legged Unit (BALLU) robots have a great potential to provide intrinsically safe interactions in environments involving humans, unlike many heavy and rigid robots. However, their unique and sensitive dynamics impose challenges to obtaining robust control policies in the real world. In this work, we demonstrate robust sim-to-real tr...Show More

Residual Physics Learning and System Identification for Sim-to-real Transfer of Policies on Buoyancy Assisted Legged Robots

Nitish Sontakke;Hosik Chae;Sangjoon Lee;Tianle Huang;Dennis W. Hong;Sehoon Hal

2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2023 | Conference Paper |

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