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+ +

The IRIS lab focuses on three reserach directions: (1) human-robot alignment, (2) contact-rich manipulation, and (3) fundamental methods in robotics. Below are some recent publications in each set of research interest. +Please visit Publications page for a full list of publications.

+ +


+
+
Human-robot alignment
+
+ +We develop methods to empower a robot with the ability to efficiently understand and be understood by human users through a variety of physical interactions. We explore how robots can aptly respond to and collaborate meaningfully with users. + +
+
+
    +
  • Robot learning from general human interactions
    • +
  • Planning and control for human-robot systems
    • +
+
+ + +
+ +
+
Safe MPC Alignment with Human Directional Feedback
+
Zhixian Xie, Wenlong Zhang, Yi Ren, Zhaoran Wang, George. J. Pappas and Wanxin Jin
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper + Code + Video + Project +
+
+
+
+ + + +
+ +
+
Learning from Human Directional Corrections
+
Wanxin Jin, Todd D Murphey, Zehui Lu, and Shaoshuai Mou
+
IEEE Transactions on Robotics (T-RO), 2023
+
+ Paper + Code + Video +
+
+
+
+ + +
+ +
+
Learning from Sparse Demonstrations
+
Wanxin Jin, Todd D Murphey, Dana Kulic, Neta Ezer, and Shaoshuai Mou
+
IEEE Transactions on Robotics (T-RO), 2023
+
+ Paper + Code + Video +
+
+
+
+ + + + +
+ +
+
Inverse Optimal Control from Incomplete Trajectory Observations
+
Wanxin Jin, Dana Kulic, Shaoshuai Mou, and Sandra Hirche
+
International Journal of Robotics Research (IJRR), 40:848–865, 2021
+
+ Paper + Code +
+
+
+
+ + + + +
+ +
+
Inverse Optimal Control for Multiphase cost functions
+
Wanxin Jin, Dana Kulic, Jonathan Lin, Shaoshuai Mou, and Sandra Hirche
+
IEEE Transactions on Robotics (T-RO), 35(6):1387–1398, 2019
+
+ Paper + Code +
+
+
+ + + +
+
+ +


+ +
+
Contact-rich manipulation
+
+ + +We aim to leverage physical principles to develop efficient representations or models for robot's physical interaction with environments. We also focus on developing algorithms to enable robots efficiently and robustly manipulate their surroundings/objects through contact. + +

+ +
    +
  • Learning, planning, and control for contact-rich manipulation
    • +
  • Computer vision and learnable geometry for dexterous manipulation
    • +
+
+ + + +
+ +
+
Task-Driven Hybrid Model Reduction for Dexterous Manipulation
+
Wanxin Jin and Michael Posa
+
IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper + Code + Video + Project +
+
+
+
+ + + + +
+ +
+
Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning
+
Wei-Cheng Huang, Alp Aydinoglu, Wanxin Jin, Michael Posa
+
IEEE International Conference on Robotics and Automation (ICRA), 2024
+
+ Paper + Video + Project +
+
+
+
+ + + +
+ +
+
Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
+
Shenao Zhang, Wanxin Jin, Zhaoran Wang
+
International Conference on Machine Learning (ICML), 2023
+
+ Paper +
+
+
+
+ + + +
+ +
+
Learning Linear Complementarity Systems
+
Wanxin Jin, Alp Aydinoglu, Mathew Halm, and Michael Posa
+
Learning for Dynamics and Control (L4DC), 2022
+
+ Paper + Code +
+
+
+ + + +
+
+ +


+ +
+
Fundamental methods in robotics
+
+ +We focus on developing fundamental theories and algorithms for achieving efficient, safe, and robust robot intelligence. Our methods lie at the intersection of model-based (control and optimization) and data-driven approaches, harnessing the complementary benefits of both. + +

+ +
    +
  • Optimal control, motion plannig, reinforcement learning
    • +
  • Differentiable optimization, inverse optimization
    • +
  • Hybrid system learning and control
    • +
+
+ + + +
+ +
+
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
+
Wanxin Jin, Zhaoran Wang, Zhuoran Yang, and Shaoshuai Mou
+
Advances in Neural Information Processing Systems (NeurIPS), 2020
+
+ Paper + Code + Video + Project +
+
+
+
+ + +
+ +
+
Safe Pontryagin Differentiable Programming
+
Wanxin Jin, Shaoshuai Mou, and George J. Pappas
+
Advances in Neural Information Processing Systems (NeurIPS), 2021
+
+ Paper + Code + Video + Project +
+
+
+
+ + +
+ +
+
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
+
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
+
IEEE Robotics and Automation Letters (RA-L), 2023
+
+ Paper + Video +
+
+
+
+ + + + +
+ +
+
Enforcing Hard Constraints with Soft Barriers: Safe-driven Reinforcement Learning in Unknown Stochastic Environments
+
Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu
+
International Conference on Machine Learning (ICML), 2023
+
+ Paper +
+
+
+
+ + +
+ +
+
A Differential Dynamic Programming Framework for Inverse Reinforcement Learning
+
Kun Cao, Xinhang Xu, Wanxin Jin, Karl H. Johansson, and Lihua Xie
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper +
+
+
+ + +
+
+ + + + + + +

+ + +:ET \ No newline at end of file diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/56/5c497dd3153a2c9684f9188c7e136bb922c7615850b884fe7280b7793ca1e0 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/56/5c497dd3153a2c9684f9188c7e136bb922c7615850b884fe7280b7793ca1e0 new file mode 100644 index 0000000..632cc49 --- /dev/null +++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/56/5c497dd3153a2c9684f9188c7e136bb922c7615850b884fe7280b7793ca1e0 @@ -0,0 +1,350 @@ +I"âE + +

+ +

The IRIS lab focuses on three reserach directions: (1) human-robot alignment, (2) contact-rich manipulation, and (3) fundamental methods in robotics. Below are some recent publications in each set of research interest. +Please visit Publications page for a full list of publications.

+ +


+
+
Human-robot alignment
+
+ +We develop methods to empower a robot with the ability to efficiently understand and be understood by human users through a variety of physical interactions. We explore how robots can aptly respond to and collaborate meaningfully with users. + +
+
+
    +
  • Robot learning from general human interactions
    • +
  • Planning and control for human-robot systems
    • +
+
+ + +
+ +
+
Safe MPC Alignment with Human Directional Feedback
+
Zhixian Xie, Wenlong Zhang, Yi Ren, Zhaoran Wang, George. J. Pappas and Wanxin Jin
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper + Code + Video + Project +
+
+
+
+ + + +
+ +
+
Learning from Human Directional Corrections
+
Wanxin Jin, Todd D Murphey, Zehui Lu, and Shaoshuai Mou
+
IEEE Transactions on Robotics (T-RO), 2023
+
+ Paper + Code + Video +
+
+
+
+ + +
+ +
+
Learning from Sparse Demonstrations
+
Wanxin Jin, Todd D Murphey, Dana Kulic, Neta Ezer, and Shaoshuai Mou
+
IEEE Transactions on Robotics (T-RO), 2023
+
+ Paper + Code + Video +
+
+
+
+ + + + +
+ +
+
Inverse Optimal Control from Incomplete Trajectory Observations
+
Wanxin Jin, Dana Kulic, Shaoshuai Mou, and Sandra Hirche
+
International Journal of Robotics Research (IJRR), 40:848–865, 2021
+
+ Paper + Code +
+
+
+
+ + + + +
+ +
+
Inverse Optimal Control for Multiphase cost functions
+
Wanxin Jin, Dana Kulic, Jonathan Lin, Shaoshuai Mou, and Sandra Hirche
+
IEEE Transactions on Robotics (T-RO), 35(6):1387–1398, 2019
+
+ Paper + Code +
+
+
+ + + +
+
+ +


+ +
+
Contact-rich manipulation
+
+ + +We aim to leverage physical principles to develop efficient representations or models for robot's physical interaction with environments. We also focus on developing algorithms to enable robots efficiently and robustly manipulate their surroundings/objects through contact. + +

+ +
    +
  • Learning, planning, and control for contact-rich manipulation
    • +
  • Computer vision and learnable geometry for dexterous manipulation
    • +
+
+ + + +
+ +
+
Task-Driven Hybrid Model Reduction for Dexterous Manipulation
+
Wanxin Jin and Michael Posa
+
IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper + Code + Video + Project +
+
+
+
+ + + + +
+ +
+
Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning
+
Wei-Cheng Huang, Alp Aydinoglu, Wanxin Jin, Michael Posa
+
IEEE International Conference on Robotics and Automation (ICRA), 2024
+
+ Paper + Video + Project +
+
+
+
+ + + +
+ +
+
Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
+
Shenao Zhang, Wanxin Jin, Zhaoran Wang
+
International Conference on Machine Learning (ICML), 2023
+
+ Paper +
+
+
+
+ + + +
+ +
+
Learning Linear Complementarity Systems
+
Wanxin Jin, Alp Aydinoglu, Mathew Halm, and Michael Posa
+
Learning for Dynamics and Control (L4DC), 2022
+
+ Paper + Code +
+
+
+ + + +
+
+ +


+ +
+
Fundamental methods in robotics
+
+ +We focus on developing fundamental theories and algorithms for achieving efficient, safe, and robust robot intelligence. Our methods lie at the intersection of model-based (control and optimization) and data-driven approaches, harnessing the complementary benefits of both. + +

+ +
    +
  • Optimal control, motion plannig, reinforcement learning
    • +
  • Differentiable optimization, inverse optimization
    • +
  • Hybrid system learning and control
    • +
+
+ + + +
+ +
+
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
+
Wanxin Jin, Zhaoran Wang, Zhuoran Yang, and Shaoshuai Mou
+
Advances in Neural Information Processing Systems (NeurIPS), 2020
+
+ Paper + Code + Video + Project +
+
+
+
+ + +
+ +
+
Safe Pontryagin Differentiable Programming
+
Wanxin Jin, Shaoshuai Mou, and George J. Pappas
+
Advances in Neural Information Processing Systems (NeurIPS), 2021
+
+ Paper + Code + Video + Project +
+
+
+
+ + +
+ +
+
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
+
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
+
IEEE Robotics and Automation Letters (RA-L), 2023
+
+ Paper + Video +
+
+
+
+ + + + +
+ +
+
Enforcing Hard Constraints with Soft Barriers: Safe-driven Reinforcement Learning in Unknown Stochastic Environments
+
Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu
+
International Conference on Machine Learning (ICML), 2023
+
+ Paper +
+
+
+ + +
+ +
+
A Differential Dynamic Programming Framework for Inverse Reinforcement Learning
+
Kun Cao, Xinhang Xu, Wanxin Jin, Karl H. Johansson, and Lihua Xie
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper +
+
+
+ + +
+
+ + + + + + +

+ + +:ET \ No newline at end of file diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/bd/7734f085a2e8047c2f458bb67a99a52dec96552310c306ad2c583e1d812bd9 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/58/f3a1eadbfa59d5e294e2be8171cb7374a3befa2cf41aeed0b6c1d615818425 similarity index 98% rename from .jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/bd/7734f085a2e8047c2f458bb67a99a52dec96552310c306ad2c583e1d812bd9 rename to .jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/58/f3a1eadbfa59d5e294e2be8171cb7374a3befa2cf41aeed0b6c1d615818425 index 83e388e..401aa75 100644 --- a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/bd/7734f085a2e8047c2f458bb67a99a52dec96552310c306ad2c583e1d812bd9 +++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/58/f3a1eadbfa59d5e294e2be8171cb7374a3befa2cf41aeed0b6c1d615818425 @@ -1,4 +1,4 @@ -I"FC +I"+C

@@ -254,7 +254,7 @@ We focus on developing fundamental theories and algorithms for achieving efficie
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
-
Submitted to IEEE Robotics and Automation Letters (RA-L), under review, 2023
+
IEEE Robotics and Automation Letters (RA-L), 2023
Paper Video diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/5f/7053f7b2b6cc7882319e03102708e21e45d716411c517572fd7897736e8d5f b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/5f/7053f7b2b6cc7882319e03102708e21e45d716411c517572fd7897736e8d5f new file mode 100644 index 0000000..be18e62 --- /dev/null +++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/5f/7053f7b2b6cc7882319e03102708e21e45d716411c517572fd7897736e8d5f @@ -0,0 +1,340 @@ +I".C + +

+ +

The IRIS lab focuses on three reserach directions: (1) human-robot alignment, (2) contact-rich manipulation, and (3) fundamental methods in robotics. Below are some recent publications in each set of research interest. +Please visit Publications page for a full list of publications.

+ +


+
+
Human-robot alignment
+
+ +We develop methods to empower a robot with the ability to efficiently understand and be understood by human users through a variety of physical interactions. We explore how robots can aptly respond to and collaborate meaningfully with users. + +
+
+
    +
  • Robot learning from general human interactions
    • +
  • Planning and control for human-robot systems
    • +
+
+ + +
+ +
+
Safe MPC Alignment with Human Directional Feedback
+
Zhixian Xie, Wenlong Zhang, Yi Ren, Zhaoran Wang, George. J. Pappas and Wanxin Jin
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper + Code + Video + Project +
+
+
+
+ + + +
+ +
+
Learning from Human Directional Corrections
+
Wanxin Jin, Todd D Murphey, Zehui Lu, and Shaoshuai Mou
+
IEEE Transactions on Robotics (T-RO), 2023
+
+ Paper + Code + Video +
+
+
+
+ + +
+ +
+
Learning from Sparse Demonstrations
+
Wanxin Jin, Todd D Murphey, Dana Kulic, Neta Ezer, and Shaoshuai Mou
+
IEEE Transactions on Robotics (T-RO), 2023
+
+ Paper + Code + Video +
+
+
+
+ + + + +
+ +
+
Inverse Optimal Control from Incomplete Trajectory Observations
+
Wanxin Jin, Dana Kulic, Shaoshuai Mou, and Sandra Hirche
+
International Journal of Robotics Research (IJRR), 40:848–865, 2021
+
+ Paper + Code +
+
+
+
+ + + + +
+ +
+
Inverse Optimal Control for Multiphase cost functions
+
Wanxin Jin, Dana Kulic, Jonathan Lin, Shaoshuai Mou, and Sandra Hirche
+
IEEE Transactions on Robotics (T-RO), 35(6):1387–1398, 2019
+
+ Paper + Code +
+
+
+ + + +
+
+ +


+ +
+
Contact-rich manipulation
+
+ + +We aim to leverage physical principles to develop efficient representations or models for robot's physical interaction with environments. We also focus on developing algorithms to enable robots efficiently and robustly manipulate their surroundings/objects through contact. + +

+ +
    +
  • Learning, planning, and control for contact-rich manipulation
    • +
  • Computer vision and learnable geometry for dexterous manipulation
    • +
+
+ + + +
+ +
+
Task-Driven Hybrid Model Reduction for Dexterous Manipulation
+
Wanxin Jin and Michael Posa
+
IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper + Code + Video + Project +
+
+
+
+ + + + +
+ +
+
Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning
+
Wei-Cheng Huang, Alp Aydinoglu, Wanxin Jin, Michael Posa
+
IEEE International Conference on Robotics and Automation (ICRA), 2024
+
+ Paper + Video + Project +
+
+
+
+ + + +
+ +
+
Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
+
Shenao Zhang, Wanxin Jin, Zhaoran Wang
+
International Conference on Machine Learning (ICML), 2023
+
+ Paper +
+
+
+
+ + + +
+ +
+
Learning Linear Complementarity Systems
+
Wanxin Jin, Alp Aydinoglu, Mathew Halm, and Michael Posa
+
Learning for Dynamics and Control (L4DC), 2022
+
+ Paper + Code +
+
+
+ + + +
+
+ +


+ +
+
Fundamental methods in robotics
+
+ +We focus on developing fundamental theories and algorithms for achieving efficient, safe, and robust robot intelligence. Our methods lie at the intersection of model-based (control and optimization) and data-driven approaches, harnessing the complementary benefits of both. + +

+ +
    +
  • Optimal control, motion plannig, reinforcement learning
    • +
  • Differentiable optimization, inverse optimization
    • +
  • Hybrid system learning and control
    • +
+
+ + + +
+ +
+
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
+
Wanxin Jin, Zhaoran Wang, Zhuoran Yang, and Shaoshuai Mou
+
Advances in Neural Information Processing Systems (NeurIPS), 2020
+
+ Paper + Code + Video + Project +
+
+
+
+ + +
+ +
+
Safe Pontryagin Differentiable Programming
+
Wanxin Jin, Shaoshuai Mou, and George J. Pappas
+
Advances in Neural Information Processing Systems (NeurIPS), 2021
+
+ Paper + Code + Video + Project +
+
+
+
+ + +
+ +
+
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
+
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
+
IEEE Robotics and Automation Letters (RA-L), 2023
+
+ Paper + Video +
+
+
+
+ + + + +
+ +
+
Enforcing Hard Constraints with Soft Barriers: Safe-driven Reinforcement Learning in Unknown Stochastic Environments
+
Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu
+
International Conference on Machine Learning (ICML), 2023
+
+ Paper +
+
+
+ + + + + +
+
+ + + + + + +

+ + +:ET \ No newline at end of file diff --git a/_pages/1.research.md b/_pages/1.research.md index 28d293e..43a5054 100644 --- a/_pages/1.research.md +++ b/_pages/1.research.md @@ -272,7 +272,7 @@ We focus on developing fundamental theories and algorithms for achieving efficie
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
-
Submitted to IEEE Robotics and Automation Letters (RA-L), under review, 2023
+
IEEE Robotics and Automation Letters (RA-L), 2023
Paper Video @@ -295,6 +295,20 @@ We focus on developing fundamental theories and algorithms for achieving efficie
+
+ + +
+ +
+
A Differential Dynamic Programming Framework for Inverse Reinforcement Learning
+
Kun Cao, Xinhang Xu, Wanxin Jin, Karl H. Johansson, and Lihua Xie
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper +
+
+
diff --git a/_site/feed.xml b/_site/feed.xml index 5c2c8e5..a55685e 100644 --- a/_site/feed.xml +++ b/_site/feed.xml @@ -1 +1 @@ -Jekyll2024-07-29T23:08:39-07:00http://localhost:4000/feed.xmlblank \ No newline at end of file +Jekyll2024-07-29T23:15:54-07:00http://localhost:4000/feed.xmlblank \ No newline at end of file diff --git a/_site/research/index.html b/_site/research/index.html index 5dfcb4a..515abe9 100644 --- a/_site/research/index.html +++ b/_site/research/index.html @@ -481,7 +481,7 @@
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
-
Submitted to IEEE Robotics and Automation Letters (RA-L), under review, 2023
+
IEEE Robotics and Automation Letters (RA-L), 2023
Paper Video @@ -504,6 +504,20 @@
+
+ + +
+ +
+
A Differential Dynamic Programming Framework for Inverse Reinforcement Learning
+
Kun Cao, Xinhang Xu, Wanxin Jin, Karl H. Johansson, and Lihua Xie
+
Submitted to IEEE Transactions on Robotics (T-RO), 2024
+
+ Paper +
+
+