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