The following is list of papers spanning perception and decision making in Robotics. These papers cover sufficient breadth to be a starter but are in no way the only representative set of papers. This list is taken from the course CS391R Robot Learning held at UT Austin in Fall 2021.
Heres a like to the papers covered in the course: https://www.cs.utexas.edu/~yukez/cs391r_fall2021/syllabus.html
3. Implicit Neural Representations with Periodic Activation Functions
4. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
5. Exploring Simple Siamese Representation Learning
6. Unsupervised Learning of Object Keypoints for Perception and Control
8. Learning to look around: Intelligently Exploring Unseen Environments for Unknown tasks
9. Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects
10. Soft Actor Critic Algorithms and Applications
11. Dream to Control: Learning Behaviors by Latent Imagination
[12. Actionable models: Unsupervised Offline Reinforcement Learning of Robotic Skills.](https://hsikchi.notion.site/12-Actionable-models-Unsupervised-Offline-Reinforcement-Learning-of-Robotic-Skills-a1ea6eef841b4b159be25fc0fe3930bf)
13. A reduction of Imitation Learning and structured prediction to no-regret online learning
14. Apprenticeship Learning via Inverse Reinforcement Learning
15. Relay Policy Learning: Solving long horizon tasks via imitation and reinforcement learning