Paper Review By Graduate Students

Fall 2023   Spring 2023   Fall 2022   Spring 2021   Fall 2020   Fall 2019   Spring 2019   Fall 2018   Spring 2018    Fall 2017

   This seminar series intends to have graduate students in the lab introduce one well-known and relevant research paper to our current research, and discuss with other lab members. In a seminar, the presenter is going to cover the following four aspects (2W+2H):

  • What this paper is about?
  • Why this paper is well-known and important to you and us?
  • How the authors formulate and solve the problem?
  • How this paper potentially benefits your and others’ research?

The papers that are discussed and presenters are listed below:
Week 1: Cao, Zhangjie, et al., “Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving”, RSS 2020, by Sangjun Lee
Week 2: Babic, Anja, et al., “Vehicle-in-the-Loop Framework for Testing Long-Term Autonomy in a Heterogeneous Marine Robot Swarm”, RAL 2020, by Jun Han
Week 3: Macchini, Matteo , et al., “Personalized Telerobotics by Fast Machine Learning of Body-Machine Interfaces”, RAL 2020], by Roman Ibrahimov
Week 4: Narayanan, Venkatraman, et al., “ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot Navigation”, IROS 2020 , by Wonse Jo
Week 5: Li, Mengxi, et al., “Learning User-Preferred Mappings for Intuitive Robot Control”, IROS 2020 ,by Jeremy Pan
Week 6: Liu, Lucia, et al., “Robot Navigation in Crowded Environments Using Deep Reinforcement Learning”, IROS 2020, by Su Sun
Week 7: Shafti, Ali, et al., “Real-World Human-Robot Collaborative Reinforcement Learning”, IROS 2020, by Goeum Cha
Week 8: Ryll, Markus, et al., “Semantic Trajectory Planning for Long-Distant Unmanned Aerial Vehicle Navigation in Urban Environments”, IROS 2020, by Shyam Sundar Kannan
Week 9: Liu , Boyi, et al., “Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems”, IROS 2019, by Manoj Raj Penmetcha