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1. Tensegrity Locomotion
2. Rearrangement Planning
3. Controlling Adaptive Hands
4. 6D Pose Estimation
5. Closing the reality gap
6. Multi-Arm Planning
7. Warehouse Automation
8. Manipulation In Clutter
9. Kinodynamic Planning


Intro to Computational Robotics (CS460/560 – Fall 2018)

This course provides a general introduction to robotics from a computational perspective with a focus on mobile robots. This includes the use of popular software for interacting with and simulating robots, such as the Robot Operating System (ROS). It will provide a view of robots as autonomous agents with a mechanical embodiment, which must observe and act upon their surroundings through the iterative execution of a sensing-planning-actuation loop. On the sensing and perception side, the course will cover state estimation challenges, such as robot localization, simultaneous localization and mapping (SLAM), as well as Bayesian solutions to these problems, such as Kalman and particle filters. For planning and decision making purposes, the course will introduce basic planning and replanning methods, such as A* and D*-like algorithms, the configuration space abstraction, sampling-based planners, and a toolbox of algorithms that solve problems by utilizing these principles. Extensions to multi-robot systems, online planning and handling uncertainty will be touched upon as well. On the control side, the course will offer an introductory coverage of robot kinematics and dynamics.

Seminar on Algorithms for Robot Manipulation (CS672 – Spring 2018)

In artificial intelligence, an intelligent agent is an autonomous entity, which observes its environment through sensors, acts upon the environment using actuators and directs its activity towards achieving goals, i.e. it is “rational”. A robot manipulator is the prototypical embodiment of an intelligent agent. Solving robot manipulation problems requires reasoning about the physical world and building upon foundational mathematical principles. At the same time, one can use as inspiration the impressive manipulation capabilities of biological organisms.

Intro to Artificial Intelligence (CS440 – Fall 2017)

The class introduces fundamental ideas that have emerged over the past fifty years of AI research. It will also provide a useful toolbox of AI algorithms. The main unifying theme is the idea of an intelligent agent: autonomous computational systems that receive percepts from the environment and perform actions or take decisions. The objective of the class is to (a) teach students how to identify the appropriate technique for designing such intelligent agents for different types of problems and (b) provide them experience in implementing such solutions on representative AI challenges.