Austin S. Wang

According to our database, Austin S. Wang authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge.

Sriram Yenamandra, Arun Ramachandran, Mukul Khanna, Karmesh Yadav, Jay Vakil, Andrew Melnik, Michael Büttner, Leon Harz, Lyon Brown, Gora Chand Nandi, Arjun P. S, Gaurav Kumar Yadav, Rahul Kala, Robert Haschke, Yang Luo, Jinxin Zhu, Yansen Han, Bingyi Lu, Xuan Gu, Qinyuan Liu, Yaping Zhao, Qiting Ye, Chenxiao Dou, Yansong Chua, Volodymyr Kuzma, Vladyslav Humennyy, Ruslan Partsey, Jonathan Francis, Devendra Singh Chaplot, Gunjan Chhablani, Alexander Clegg, Théophile Gervet, Vidhi Jain, Ram Ramrakhya, Andrew Szot, Austin S. Wang, Tsung-Yen Yang, Aaron Edsinger, Charles C. Kemp, Binit Shah, Zsolt Kira, Dhruv Batra, Roozbeh Mottaghi, Yonatan Bisk, Chris Paxton

CoRR, 2024

2023

USA-Net: Unified Semantic and Affordance Representations for Robot Memory.

Benjamin Bolte, Austin S. Wang, Jimmy Yang, Mustafa Mukadam, Mrinal Kalakrishnan, Chris Paxton

IROS, 2023

Navigating to Objects Specified by Images.

Jacob Krantz, Théophile Gervet, Karmesh Yadav, Austin S. Wang, Chris Paxton, Roozbeh Mottaghi, Dhruv Batra, Jitendra Malik, Stefan Lee, Devendra Singh Chaplot

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

HomeRobot: Open-Vocabulary Mobile Manipulation.

Sriram Yenamandra, Arun Ramachandran, Karmesh Yadav, Austin S. Wang, Mukul Khanna, Théophile Gervet, Tsung-Yen Yang, Vidhi Jain, Alexander Clegg, John M. Turner, Zsolt Kira, Manolis Savva, Angel X. Chang, Devendra Singh Chaplot, Dhruv Batra, Roozbeh Mottaghi, Yonatan Bisk, Chris Paxton

Proceedings of the Conference on Robot Learning, 2023

2022

Efficient and Interpretable Robot Manipulation With Graph Neural Networks.

Yixin Lin, Austin S. Wang, Eric Undersander, Akshara Rai

IEEE Robotics Autom. Lett., 2022

Differentiable and Learnable Robot Models.

Franziska Meier, Austin S. Wang, Giovanni Sutanto, Yixin Lin, Paarth Shah

CoRR, 2022

Theseus: A Library for Differentiable Nonlinear Optimization.

Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi, Ricky T. Q. Chen, Joseph Ortiz, Daniel DeTone, Austin S. Wang, Stuart Anderson, Jing Dong, Brandon Amos, Mustafa Mukadam

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Efficient and Interpretable Robot Manipulation with Graph Neural Networks.

Yixin Lin, Austin S. Wang, Akshara Rai

CoRR, 2021

RB2: Robotic Manipulation Benchmarking with a Twist.

Sudeep Dasari, Jianren Wang, Joyce Hong, Shikhar Bahl, Yixin Lin, Austin S. Wang, Abitha Thankaraj, Karanbir Chahal, Berk Çalli, Saurabh Gupta, David Held, Lerrel Pinto, Deepak Pathak, Vikash Kumar, Abhinav Gupta

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Encoding Physical Constraints in Differentiable Newton-Euler Algorithm.

Giovanni Sutanto, Austin S. Wang, Yixin Lin, Mustafa Mukadam, Gaurav S. Sukhatme, Akshara Rai, Franziska Meier

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Learning State-Dependent Losses for Inverse Dynamics Learning.

Kristen Morse, Neha Das, Yixin Lin, Austin S. Wang, Akshara Rai, Franziska Meier

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2019

Homography-Based Deep Visual Servoing Methods for Planar Grasps.

Austin S. Wang, Wuming Zhang, Daniel Troniak, Jacky Liang, Oliver Kroemer

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Learning Robust Manipulation Strategies with Multimodal State Transition Models and Recovery Heuristics.

Austin S. Wang, Oliver Kroemer

Proceedings of the International Conference on Robotics and Automation, 2019