b'Jie Tan'

research

∙ 07/31/2023

Discovering Adaptable Symbolic Algorithms from Scratch

Autonomous robots deployed in the real world will need control policies ...

0 Stephen Kelly, et al. ∙

research

∙ 06/24/2023

Transforming a Quadruped into a Guide Robot for the Visually Impaired: Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism

This paper explores the principles for transforming a quadrupedal robot ...

0 J. Taery Kim, et al. ∙

research

∙ 06/16/2023

CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controller

We present CAJun, a novel hierarchical learning and control framework th...

0 Yuxiang Yang, et al. ∙

research

∙ 06/15/2023

Datasets and Benchmarks for Offline Safe Reinforcement Learning

This paper presents a comprehensive benchmarking suite tailored to offli...

0 Zuxin Liu, et al. ∙

research

∙ 06/14/2023

Language to Rewards for Robotic Skill Synthesis

Large language models (LLMs) have demonstrated exciting progress in acqu...

0 Wenhao Yu, et al. ∙

research

∙ 06/13/2023

SayTap: Language to Quadrupedal Locomotion

Large language models (LLMs) have demonstrated the potential to perform ...

0 Yujin Tang, et al. ∙

research

∙ 05/24/2023

Barkour: Benchmarking Animal-level Agility with Quadruped Robots

Animals have evolved various agile locomotion strategies, such as sprint...

2 Ken Caluwaerts, et al. ∙

research

∙ 05/01/2023

IndoorSim-to-OutdoorReal: Learning to Navigate Outdoors without any Outdoor Experience

We present IndoorSim-to-OutdoorReal (I2O), an end-to-end learned visual ...

0 Joanne Truong, et al. ∙

research

∙ 04/17/2023

Continuous Versatile Jumping Using Learned Action Residuals

Jumping is essential for legged robots to traverse through difficult ter...

5 Yuxiang Yang, et al. ∙

research

∙ 03/23/2023

On Designing a Learning Robot: Improving Morphology for Enhanced Task Performance and Learning

As robots become more prevalent, optimizing their design for better perf...

0 Maks Sorokin, et al. ∙

research

∙ 02/02/2023

Mnemosyne: Learning to Train Transformers with Transformers

Training complex machine learning (ML) architectures requires a compute ...

0 Deepali Jain, et al. ∙

research

∙ 12/06/2022

Efficient Learning of Voltage Control Strategies via Model-based Deep Reinforcement Learning

This article proposes a model-based deep reinforcement learning (DRL) me...

0 Ramij R. Hossain, et al. ∙

research

∙ 10/19/2022

Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization

We propose a framework to enable multipurpose assistive mobile robots to...

5 Thomas Lew, et al. ∙

research

∙ 09/22/2022

Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation

Despite decades of research, existing navigation systems still face real...

16 Xuesu Xiao, et al. ∙

research

∙ 07/27/2022

PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations

Evolution Strategy (ES) algorithms have shown promising results in train...

0 Kuang-Huei Lee, et al. ∙

research

∙ 06/27/2022

Learning Semantics-Aware Locomotion Skills from Human Demonstration

The semantics of the environment, such as the terrain type and property,...

10 Yuxiang Yang, et al. ∙

research

∙ 05/29/2022

On the Robustness of Safe Reinforcement Learning under Observational Perturbations

Safe reinforcement learning (RL) trains a policy to maximize the task re...

0 Zuxin Liu, et al. ∙

research

∙ 04/08/2022

Multi-objective evolution for Generalizable Policy Gradient Algorithms

Performance, generalizability, and stability are three Reinforcement Lea...

0 Juan Jose Garau Luis, et al. ∙

research

∙ 03/05/2022

Safe Reinforcement Learning for Legged Locomotion

Designing control policies for legged locomotion is complex due to the u...

0 Tsung-Yen Yang, et al. ∙

research

∙ 12/07/2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance

Safe exploration is critical for using reinforcement learning (RL) in ri...

19 Michael Luo, et al. ∙

research

∙ 11/29/2021

Physics-informed Evolutionary Strategy based Control for Mitigating Delayed Voltage Recovery

In this work we propose a novel data-driven, real-time power system volt...

0 Yan Du, et al. ∙

research

∙ 10/12/2021

Does it matter who pays back Technical Debt? An empirical study of self-fixed TD

Context: Technical Debt (TD) can be paid back either by those that incur...

0 Jie Tan, et al. ∙

research

∙ 10/11/2021

Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World

Legged robots are physically capable of traversing a wide range of chall...

0 Laura Smith, et al. ∙

research

∙ 09/12/2021

Learning to Navigate Sidewalks in Outdoor Environments

Outdoor navigation on sidewalks in urban environments is the key technol...

0 Maks Sorokin, et al. ∙

research

∙ 06/22/2021

Do practitioners intentionally self-fix Technical Debt and why?

The impact of Technical Debt (TD) on software maintenance and evolution ...

0 Jie Tan, et al. ∙

research

∙ 04/13/2021

Disentangled Motif-aware Graph Learning for Phrase Grounding

In this paper, we propose a novel graph learning framework for phrase gr...

0 Zongshen Mu, et al. ∙

research

∙ 04/09/2021

Fast and Efficient Locomotion via Learned Gait Transitions

We focus on the problem of developing efficient controllers for quadrupe...

3 Yuxiang Yang, et al. ∙

research

∙ 02/04/2021

How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned

Deep reinforcement learning (RL) has emerged as a promising approach for...

48 Julian Ibarz, et al. ∙

research

∙ 01/15/2021

SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning

As learning-based approaches progress towards automating robot controlle...

0 Yifeng Jiang, et al. ∙

research

∙ 01/13/2021

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more u...

0 Renke Huang, et al. ∙

research

∙ 11/11/2020

Learning Agile Locomotion Skills with a Mentor

Developing agile behaviors for legged robots remains a challenging probl...

0 Atil Iscen, et al. ∙

research

∙ 11/11/2020

Zero-Shot Terrain Generalization for Visual Locomotion Policies

Legged robots have unparalleled mobility on unstructured terrains. Howev...

0 Alejandro Escontrela, et al. ∙

research

∙ 10/27/2020

Learning to be Safe: Deep RL with a Safety Critic

Safety is an essential component for deploying reinforcement learning (R...

3 Krishnan Srinivasan, et al. ∙

research

∙ 08/03/2020

Learning Agile Locomotion via Adversarial Training

Developing controllers for agile locomotion is a long-standing challenge...

5 Yujin Tang, et al. ∙

research

∙ 04/02/2020

Learning Agile Robotic Locomotion Skills by Imitating Animals

Reproducing the diverse and agile locomotion skills of animals has been ...

0 Xue Bin Peng, et al. ∙

research

∙ 03/15/2020

Cooperation without Coordination: Hierarchical Predictive Planning for Decentralized Multiagent Navigation

Decentralized multiagent planning raises many challenges, such as adapti...

8 Rose E. Wang, et al. ∙

research

∙ 03/02/2020

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning

Learning adaptable policies is crucial for robots to operate autonomousl...

6 Xingyou Song, et al. ∙

research

∙ 02/20/2020

Learning to Walk in the Real World with Minimal Human Effort

Reliable and stable locomotion has been one of the most fundamental chal...

27 Sehoon Ha, et al. ∙

research

∙ 10/07/2019

Policies Modulating Trajectory Generators

We propose an architecture for learning complex controllable behaviors b...

12 Atil Iscen, et al. ∙

research

∙ 09/28/2019

Learning Fast Adaptation with Meta Strategy Optimization

The ability to walk in new scenarios is a key milestone on the path towa...

0 Wenhao Yu, et al. ∙

research

∙ 09/27/2019

Zero-shot Imitation Learning from Demonstrations for Legged Robot Visual Navigation

Imitation learning is a popular approach for training effective visual n...

19 Xinlei Pan, et al. ∙

research

∙ 09/26/2019

Autonomous Control of a Tendon-driven Robotic Limb with Elastic Elements Reveals that Added Elasticity can Enhance Learning

Passive elastic elements can contribute to stability, energetic efficien...

0 Ali Marjaninejad, et al. ∙

research

∙ 07/08/2019

Data Efficient Reinforcement Learning for Legged Robots

We present a model-based framework for robot locomotion that achieves wa...

6 Yuxiang Yang, et al. ∙

research

∙ 03/09/2019

Adaptive Power System Emergency Control using Deep Reinforcement Learning

Power system emergency control is generally regarded as the last safety ...

0 Qiuhua Huang, et al. ∙

research

∙ 03/04/2019

NoRML: No-Reward Meta Learning

Efficiently adapting to new environments and changes in dynamics is crit...

28 Yuxiang Yang, et al. ∙

research

∙ 12/26/2018

Learning to Walk via Deep Reinforcement Learning

Deep reinforcement learning suggests the promise of fully automated lear...

30 Tuomas Haarnoja, et al. ∙

research

∙ 12/13/2018

Soft Actor-Critic Algorithms and Applications

Model-free deep reinforcement learning (RL) algorithms have been success...

12 Tuomas Haarnoja, et al. ∙

research

∙ 05/20/2018

Optimizing Simulations with Noise-Tolerant Structured Exploration

We propose a simple drop-in noise-tolerant replacement for the standard ...

0 Krzysztof Choromanski, et al. ∙

research

∙ 04/27/2018

Sim-to-Real: Learning Agile Locomotion For Quadruped Robots

Designing agile locomotion for quadruped robots often requires extensive...

0 Jie Tan, et al. ∙

research

∙ 03/03/2017

Large-Scale Evolution of Image Classifiers

Neural networks have proven effective at solving difficult problems but ...

0 Esteban Real, et al. ∙

Jie Tan

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