Robotics: Algorithms and Applications

MW 3:00-4:20, ARC G070

Instructor: Tapomayukh Bhattacharjee
OH: Thursday 3-4pm, CSE2 277

TA: Brian Hou
TA: Aditya Vamsikrishna Mandalika
OH: Monday 2-3pm, CSE2 152; Wednesday 2-3pm, CSE2 276

Canvas: https://canvas.uw.edu/courses/1270226
Piazza: https://piazza.com/washington/winter2019/cse571

Overview

Prerequisites: familiarity with mathematical proofs, probability, linear algebra, programming
Grading: Homeworks (60%), Project (30%), Class participation (10%)
Textbooks (optional):

Probabilistic Robotics, S. Thrun, W. Burgard, and D. Fox. MIT Press, Cambridge, MA, 2005.

Planning Algorithms, Steven M. LaValle. Cambridge University Press.

Artificial Intelligence: A Modern Approach (Third Edition), Russell, Stuart J., and Peter Norvig. Pearson Education Limited, 2016.

Automated Planning: Theory and Practice, Malik Ghallab, Dana Nau, Paolo Traverso. Elsevier, 2004.

Feedback Systems: An Introduction for Scientists and Engineers, Aström, K. J., & Murray, R. M. Princeton University Press, 2018.

Reinforcement Learning: An Introduction, R.S. Sutton and A.G. Barto. MIT Press, Cambridge, MA, 2018.

Assignments

Homework assignments will have both written and programming components. Discussion is encouraged, but each student must independently write up and implement their solutions. All collaborators must be listed on each submission.

Assignments are due online by 11:59 PM on the listed date. Each student has four free late days for the two assignments; if an assignment is submitted after exhausting the late days, it is subject to a 10-point penalty for each day over the budget.

• Homework #1, due Thursday, Jan. 31 (pdf, tex, code)
• Homework #2, due Monday, Mar. 11 (pdf, tex, code)

Writeups must be submitted as a PDF via Gradescope. LaTeX is preferred, but other typesetting methods are acceptable. Code for the programming component must be submitted in a zip archive via Canvas.

Project

Research projects will be completed in teams of three. Students are encouraged to explore any ideas related to robotics or from their own research. Project deliverables and suggested project ideas are now available here.

• Proposal, due Monday, Jan. 28
• Progress report, due Thursday, Feb. 28
• Poster session, Thursday, Mar. 21 2:30-4:20pm
• Final report, due Friday, Mar. 22

Project proposals, progress reports, posters, and final reports must be submitted via Gradescope.

Final Projects

• Enhancing Slam with Dynamic Object Attention (Adam Fishman, Junha Roh, Maxwell Horton)
• Generating dance moves in a humanoid from music (Divye Pratap Jain, Akshat Shrivastava, Andrew Li)
• A Multi-functional Car for SLAM & Trajectory Tracking (Anyi Chen, Hui Fu, Hyunjin Cho)
• Local Collision Avoidance for a Nano-drone (Bindita Chaudhuri, Chung Yi Weng, Melanie Anderson)
• Baseball-Bot: Deep RL and Sim-Real Transfer on a Real Robot (Boling Yang, Xiangyun Meng, Felix Leeb)
• Handover System Based on HERB Robot Arm (Chen Gong, Zeyu Jin)
• Wanderer 16: Navigating Around the Basement (Isaac Ahn, Liangwu Yan, Meixin Zhu)
• Selecting Bite Acquisition Strategies from Food Properties and Positions (Gilwoo Lee, Ethan Gordon, Matt Schmittle)
• Embedding Object Labels in the Map for Semantic Mapping on Mobile Robot (Kousuke Ariga, Chi-Heng Hung, Yao-Chung Liang)
• Safe Person Following using the RACECAR (Ken Latimer, Ivan Evtimov)
• End Effector Imitation Learning for Food Manipulation (Liyiming Ke)
• Comparison of Particle Based Filtering Algorithms in Localization (Henry Lu, Kevin Lin, Ricky Zhang)
• A Person-Following Robot (Nansong Yi, Thomas Wang, Ollin Boer Bohan)
• Implementing Markov Decision Process for Path Planning (Niyousha Rahimi)
• Optimizing Motion-Planning Problem Setup via Bounded Evaluation with Application to Following Surgical Trajectories (Sherdil Niyaz)
• Desk Organization via Relational Learning & Multimodal Inputs (Shivam Singhal)

Schedule