Benjamin Alt

Writing

ICRA 2021 Reading List

My personal post-ICRA 2021 reading list with papers I came across while attending the conference and which I particularly want to read. It is also intended as a resource for my colleagues who did not attend ICRA this year.

reading-listrobotics

This is my personal post-ICRA 2021 reading list with papers I came across while attending the conference and which I particularly want to read. It is also intended as a resource for my colleagues who did not attend ICRA this year.

Most papers will be about task- or motion-level robot learning, but many intersect with other domains as well. If you presented a paper at ICRA you think I would like and it is not on this list, please send me an email and I promise to read it!

Highlighted are papers I read (or attended the presentation) and found especially insightful. This list is subject to change as I read my way through it or add more from the proceedings.

2021

Thibaut Kulak, Hakan Girgin, Jean-Marc Odobez, and

IEEE Robotics and Automation Letters, Apr 2021

Auto-Tuned Sim-to-Real Transfer

Yuqing Du, Olivia Watkins, Trevor Darrell, and

arXiv:2104.07662 [cs], May 2021

Learning Geometric Reasoning and Control for Long-Horizon Tasks from Visual Input

Danny Driess, Jung-Su Ha, Russ Tedrake, and

In 2021 IEEE International Conference on Robotics and Automation (ICRA), May 2021

Shen Li, Daehyung Park, Yoonchang Sung, and

arXiv:2103.14464 [cs], Mar 2021

Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast

Srikanth Malla, Chiho Choi, and Behzad Dariush

arXiv:2011.04853 [cs], Mar 2021

Samuele Tosatto, Georgia Chalvatzaki, and Jan Peters

arXiv:2010.13766 [cs], May 2021

Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes

Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, and

arXiv:2103.14127 [cs], Mar 2021

Sparsity-Inducing Optimal Control via Differential Dynamic Programming

Traiko Dinev, Wolfgang Merkt, Vladimir Ivan, and

arXiv:2011.07325 [cs], Mar 2021

Self-Imitation Learning by Planning

Sha Luo, Hamidreza Kasaei, and Lambert Schomaker

arXiv:2103.13834 [cs], Mar 2021

Èric Pairet, Constantinos Chamzas, Yvan Petillot, and

IEEE Robot. Autom. Lett., Apr 2021

End-To-End Semi-supervised Learning for Differentiable Particle Filters

Hao Wen, Xiongjie Chen, Georgios Papagiannis, and

arXiv:2011.05748 [cs, stat], Mar 2021

Representation Matters: Improving Perception and Exploration for Robotics

Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, and

arXiv:2011.01758 [cs, stat], Mar 2021

Deep Structured Reactive Planning

Jerry Liu, Wenyuan Zeng, Raquel Urtasun, and

arXiv:2101.06832 [cs], Apr 2021

Batch Exploration with Examples for Scalable Robotic Reinforcement Learning

Annie S. Chen, HyunJi Nam, Suraj Nair, and

IEEE Robot. Autom. Lett., Jul 2021

Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning

Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, and

arXiv:2103.13842 [cs], Mar 2021

Causal Reasoning in Simulation for Structure and Transfer Learning of Robot Manipulation Policies

Timothy E. Lee, Jialiang Zhao, Amrita S. Sawhney, and

arXiv:2103.16772 [cs], Mar 2021

LASER: Learning a Latent Action Space for Efficient Reinforcement Learning

Arthur Allshire, Roberto Martín-Martín, Charles Lin, and

arXiv:2103.15793 [cs], Mar 2021

Thomas Power, and Dmitry Berenson

arXiv:2102.02493 [cs], Feb 2021

Towards Personalized Explanation of Robot Path Planning via User Feedback

Kayla Boggess, Shenghui Chen, and Lu Feng

arXiv:2011.00524 [cs], Mar 2021

Coarse-to-Fine Imitation Learning: Robot Manipulation from a Single Demonstration

Edward Johns

arXiv:2105.06411 [cs], May 2021

A Weighted Method for Fast Resolution of Strictly Hierarchical Robot Task Specifications Using Exact Penalty Functions

Ajay Suresha Sathya, Goele Pipeleers, Wilm Decré, and

IEEE Robotics and Automation Letters, Apr 2021

Human-robot collaborative object transfer using human motion prediction based on Cartesian pose Dynamic Movement Primitives

Antonis Sidiropoulos, Yiannis Karayiannidis, and Zoe Doulgeri

arXiv:2104.03155 [cs], Apr 2021

Adversarial Training is Not Ready for Robot Learning

Mathias Lechner, Ramin Hasani, Radu Grosu, and

arXiv:2103.08187 [cs], Mar 2021

Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning

Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, and

arXiv:2011.08345 [cs], Apr 2021

2020

Andrei Haidu, and Michael Beetz

arXiv:2011.13689 [cs], Nov 2020

RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer

Daniel Ho, Kanishka Rao, Zhuo Xu, and

arXiv:2011.03148 [cs], Nov 2020

LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting

Gregory P. Meyer, Jake Charland, Shreyash Pandey, and

arXiv:2003.05982 [cs], Oct 2020

Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization

M. Tuluhan Akbulut, Utku Bozdogan, Ahmet Tekden, and

arXiv:2011.04282 [cs], Nov 2020

MS-RANAS: Multi-Scale Resource-Aware Neural Architecture Search

Cristian Cioflan, and Radu Timofte

arXiv:2009.13940 [cs], Sep 2020

Sarah Bechtle, Bilal Hammoud, Akshara Rai, and

arXiv:2011.03859 [cs], Nov 2020

Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models

Yuchen Wu, Melissa Mozifian, and Florian Shkurti

arXiv:2011.01298 [cs], Nov 2020

Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning

Michael Lutter, Johannes Silberbauer, Joe Watson, and

arXiv:2011.01734 [cs], Nov 2020

2019

IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks

Youngwoon Lee, Edward S. Hu, Zhengyu Yang, and

arXiv:1911.07246 [cs], Nov 2019