Seminal Papers in Robotics

Real world robotics

1. R. R. Murphy, “Human-robot interaction in rescue robotics,” IEEE Trans. Syst. Man Cybern. Part C Appl. Rev., vol. 34, no. 2, pp. 138–153, 2004..
2. F. Martin, “Real Robots Don’t Drive Straight,” AAAI Spring Symp. Robot. Robot Venues Resour. AI Educ., 2007

General Robotics

1. T. Niemueller and S. Widyadharma, “Artificial Intelligence – An Introduction to Robotics,” Artif. Intell., pp. 1–14, 2003.

Navigation

• Wall Following for Autonomous Navigation
• S. Riisgaard and M. R. Blas, “SLAM for Dummies A Tutorial Approach to Simultaneous Localization and Mapping,” A Tutor. Approach to Simultaneous Localization Mapp., vol. 22, no. June, pp. 1–127, 2004.

Artificial Intelligence

• R. A. Watson, S. G. Ficiei, and J. B. Pollack, “Embodied evolution: Embodying an evolutionary algorithm in a population of robots”.
• Route Assignment for Autonomous Vehicles

Fiducials

• E. Olson, “AprilTag: A robust and flexible visual fiducial system,” Proc. - IEEE Int. Conf. Robot. Autom., pp. 3400–3407, 2011.
• L. Ross, “Fiducial Marker Navigation for Mobile Robots,”

Robot Behavior

1. De Silva and H. Ekanayake, “Behavior-based robotics and the reactive paradigm: A survey,” Proc. 11th Int. Conf.
2. Brooks - Robust Layered Control System for a Mobile Robot.

Additional Papers

• Video: Learn basics about Quaternions. Visualizing Quaternions and Quaternions.
• Arkin - Motor Schema-Based Mobile Robot Navigation
• Grabowski - Heterogeneous Teams of Modular Robots for Mapping and Exploration
• FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem
• An Evaluation of the RGB-D SLAM System
• LSD-SLAM: Large-Scale Direct Monocular SLAM Robotics
• Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow
• DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks
• The Dynamic Window Approach to Collision Avoidance Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events
• Probablistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces
• Rapidly-Exploring Random Trees: A New Tool for Path Planning
• RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments
• [L. De Silva and H. Ekanayake, “Behavior-based robotics and the reactive paradigm: A survey,” Proc. 11th Int. Conf. Comput. Inf. Technol. ICCIT 2008, pp. 36–43, 2008.]

List of other resources

1. Videos curated by instructor: Youtube cosi119a playlist
2. Podcast about Self-Driving Deep Learning - A really good background about applying deep learning to autonomous navigation. Just 1 hour.
3. DataCamp. This is an amazing site for learning Python and other useful Data science skills. If you are looking to brush up or learn new skills, you should definitely consider signing up!
4. Artificial Intelligence for Robotics - A fantastic introduction to the basics of SLAM and localization, doing some of the elementary mathematics that is the foundation of this core technique in navigation.
5. I like this overview of good Python Style. This is the official Python Style Guide
6. Columbia edX Course on Robotics and ROS: This is an extensive and excellent course on Robotics with ROS, the Robot Operating System. I have followed it all and found that it is helpful in many different ways. You should follow the whole thing during the first 3 weeks of the course.
7. MIT Self Driving Cars Course is a great online course consisting of lectures and other content. I recommend you purusing it!
8. From ETH Zurich course Programming for Robots. From my review this looks like a nice video introduction and review of ROS. Here are the Slides and videos
9. Our new Robot platform is a Turtlebot 2. Even though the number is lower, it should be more powerful and more reliable. Learning the TurtleBot and ROS is an excellent guide.

Sources

• Papers we love repository
• Course notes from Professor Carlotta Berry of Rose-Hulman Institute of Technology, and the course in Mobile Robotics
• Annotated Bibliography