STANFORD

 CS294B/CS294W
 Project Suggestions


Below is a list of some project ideas for the class. You're also welcome to propose your own STAIR-related project. We'll pick projects in the class' first meeting.
  1. Perception (vision) for robotic manipulation.
    In robotics, it is a fairly "easy" problem to pick up many objects so long as we have a detailed 3D CAD model of the object. However, if we are seeing a new object for the first time through our camera, it is then a very hard problem just to figure out how to pick the object up. In this project, we will develop computer vision algorithms for STAIR that learn to to pick up any ordinary, home or office object (such as staplers, cups, pens, a hammer, pliers, etc).

  2. Spoken dialog for STAIR.
    We want STAIR to be able to understand and execute verbal/spoken commands such as: In this project, we'll develop a spoken dialog system that can understand such commands. The emphasis of this project will be the speech understanding (rather than speech recognition).

  3. Indoor robot navigation.
    We want STAIR to be able to safely go anywhere within the Stanford Gates building. For this, one of the most crucial capabilities for the robot will be efficient and precise navigation in close proximity to obstacles. Compared to most indoor robots, we will require significantly more precise navigation and localization, to enable tasks such as manipulating (opening) a door handle. In this project, we'll implement high-accuracy localization and navigation algorithms for STAIR.

  4. Mapping the Gates building.
    In order to go anywhere within the Gates building, STAIR will need a map of the building that is annotated with objects (such as doors and elevators that it can use). This project will focus on mapping out (using STAIR's laser scanner) the Gates building, creating precise models of objects, and annotating the Gates map with these objects.

  5. Opening doors and pushing elevator buttons.
    In order to go anywhere in Gates, STAIR will need to be able to open doors and push elevator buttons. We will develop robotic manipulation algorithms for opening doors and pushing elevator buttons. In either case, the basic approach will be to use either computer vision or the laser scanner to localize the robot precisely relative to a specific door handle or the elevator button, and then reaching out to perform the manipulation task.

  6. Computer vision: Fast, robust object recognition. We would like STAIR to understand a large vocabulary of objects in everyday home and office environments. To enable this, we will use a "cascade" (linear chain) of classifiers that quickly rejects pictures that do not contain any interesting object. We will implement the Wu/Rehg cascade of classifiers, and extend it to multi-class object recognition for STAIR.

  7. Computer vision: Segmentation from parallax. Segmentation is often considered a key step in object recognition and scene understanding. We will develop a novel algorithm that uses stereo (two cameras) and/or parallax (different images resulting from motion of the robot) to create a basis for segmentation. Unlike traditional segmentation algorithms, we will therefore exploit cues other than color to perform the task.

  8. Seeing itself. For an intelligent robot, part of understanding the perceived images means being able to see and understand images of itself---specifically, its own hand/arm. We will develop a reliable system for recognizing the robot's own arm in the video. This will be done using both kinesthetic information about the position of the arm, as well as the appearance of the arm as it moves around in the image.

  9. Propose your own.
    You are also very welcome to propose any other research project that is relevant to STAIR.


Comments to cs294b-qa@cs.stanford.edu.

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