ICRA 2021 Reading List

Created in June 03, 2021

2021   ·   reading-list   robotics   ·   reading-list

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

  1. Active Learning of Bayesian Probabilistic Movement Primitives
    Thibaut Kulak, Hakan Girgin, Jean-Marc Odobez, and 1 more author
    IEEE Robotics and Automation Letters, Apr 2021
    DOI
  2. Auto-Tuned Sim-to-Real Transfer
    Yuqing Du, Olivia Watkins, Trevor Darrell, and 2 more authors
    arXiv:2104.07662 [cs], May 2021
  3. Learning Geometric Reasoning and Control for Long-Horizon Tasks from Visual Input
    Danny Driess, Jung-Su Ha, Russ Tedrake, and 1 more author
    In 2021 IEEE International Conference on Robotics and Automation (ICRA), May 2021
    DOI
  4. Reactive Task and Motion Planning under Temporal Logic Specifications
    Shen Li, Daehyung Park, Yoonchang Sung, and 2 more authors
    arXiv:2103.14464 [cs], Mar 2021
  5. Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast
    Srikanth Malla, Chiho Choi, and Behzad Dariush
    arXiv:2011.04853 [cs], Mar 2021
  6. Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills
    Samuele Tosatto, Georgia Chalvatzaki, and Jan Peters
    arXiv:2010.13766 [cs], May 2021
  7. Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes
    Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, and 1 more author
    arXiv:2103.14127 [cs], Mar 2021
  8. Sparsity-Inducing Optimal Control via Differential Dynamic Programming
    Traiko Dinev, Wolfgang Merkt, Vladimir Ivan, and 2 more authors
    arXiv:2011.07325 [cs], Mar 2021
  9. Self-Imitation Learning by Planning
    Sha Luo, Hamidreza Kasaei, and Lambert Schomaker
    arXiv:2103.13834 [cs], Mar 2021
  10. Path Planning for Manipulation using Experience-driven Random Trees
    Èric Pairet, Constantinos Chamzas, Yvan Petillot, and 1 more author
    IEEE Robot. Autom. Lett., Apr 2021
    DOI
  11. End-To-End Semi-supervised Learning for Differentiable Particle Filters
    Hao Wen, Xiongjie Chen, Georgios Papagiannis, and 2 more authors
    arXiv:2011.05748 [cs, stat], Mar 2021
  12. Representation Matters: Improving Perception and Exploration for Robotics
    Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, and 8 more authors
    arXiv:2011.01758 [cs, stat], Mar 2021
  13. Deep Structured Reactive Planning
    Jerry Liu, Wenyuan Zeng, Raquel Urtasun, and 1 more author
    arXiv:2101.06832 [cs], Apr 2021
  14. Batch Exploration with Examples for Scalable Robotic Reinforcement Learning
    Annie S. Chen, HyunJi Nam, Suraj Nair, and 1 more author
    IEEE Robot. Autom. Lett., Jul 2021
    DOI
  15. Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning
    Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, and 3 more authors
    arXiv:2103.13842 [cs], Mar 2021
  16. Causal Reasoning in Simulation for Structure and Transfer Learning of Robot Manipulation Policies
    Timothy E. Lee, Jialiang Zhao, Amrita S. Sawhney, and 2 more authors
    arXiv:2103.16772 [cs], Mar 2021
  17. LASER: Learning a Latent Action Space for Efficient Reinforcement Learning
    Arthur Allshire, Roberto Martín-Martín, Charles Lin, and 3 more authors
    arXiv:2103.15793 [cs], Mar 2021
  18. Keep it Simple: Data-efficient Learning for Controlling Complex Systems with Simple Models
    Thomas Power, and Dmitry Berenson
    arXiv:2102.02493 [cs], Feb 2021
  19. Towards Personalized Explanation of Robot Path Planning via User Feedback
    Kayla Boggess, Shenghui Chen, and Lu Feng
    arXiv:2011.00524 [cs], Mar 2021
  20. Coarse-to-Fine Imitation Learning: Robot Manipulation from a Single Demonstration
    Edward Johns
    arXiv:2105.06411 [cs], May 2021
  21. A Weighted Method for Fast Resolution of Strictly Hierarchical Robot Task Specifications Using Exact Penalty Functions
    Ajay Suresha Sathya, Goele Pipeleers, Wilm Decré, and 1 more author
    IEEE Robotics and Automation Letters, Apr 2021
    DOI
  22. 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
  23. Adversarial Training is Not Ready for Robot Learning
    Mathias Lechner, Ramin Hasani, Radu Grosu, and 2 more authors
    arXiv:2103.08187 [cs], Mar 2021
  24. Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning
    Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, and 2 more authors
    arXiv:2011.08345 [cs], Apr 2021

2020

  1. Automated acquisition of structured, semantic models of manipulation activities from human VR demonstration
    Andrei Haidu, and Michael Beetz
    arXiv:2011.13689 [cs], Nov 2020
  2. RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer
    Daniel Ho, Kanishka Rao, Zhuo Xu, and 3 more authors
    arXiv:2011.03148 [cs], Nov 2020
  3. LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
    Gregory P. Meyer, Jake Charland, Shreyash Pandey, and 4 more authors
    arXiv:2003.05982 [cs], Oct 2020
  4. Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization
    M. Tuluhan Akbulut, Utku Bozdogan, Ahmet Tekden, and 1 more author
    arXiv:2011.04282 [cs], Nov 2020
  5. MS-RANAS: Multi-Scale Resource-Aware Neural Architecture Search
    Cristian Cioflan, and Radu Timofte
    arXiv:2009.13940 [cs], Sep 2020
  6. Leveraging Forward Model Prediction Error for Learning Control
    Sarah Bechtle, Bilal Hammoud, Akshara Rai, and 2 more authors
    arXiv:2011.03859 [cs], Nov 2020
  7. Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models
    Yuchen Wu, Melissa Mozifian, and Florian Shkurti
    arXiv:2011.01298 [cs], Nov 2020
  8. Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning
    Michael Lutter, Johannes Silberbauer, Joe Watson, and 1 more author
    arXiv:2011.01734 [cs], Nov 2020

2019

  1. IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
    Youngwoon Lee, Edward S. Hu, Zhengyu Yang, and 2 more authors
    arXiv:1911.07246 [cs], Nov 2019


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