From the monthly archives: October 2011
Markov Localization (pp. 301-314)
Markov localization is one form of probabilistic map-based localization. The basic function of map-based localization is to provide the robot with its most likely location in a known map. Since all the sensors that allow a robot to interact with its environment are subject to error, we will never know with [...]
The deadline for Robotics: Science and Systems is on January 30, 2012. The conference will be held in Sidney, Australia.
The deadline for the 25th International Conference on Intelligent Robots and Systems is on March 10, 2012. The conference will be held at the Algarve, Portugal.
CS undergrad Daniel Zukowski, Math major Dan Davis-Boxleitner and Physics undergraduate Todd Bernhard obtained $2400 in support from CU Boulder’s UROP program for the project
“Identifying plant growth characteristics in an automated hydroponics system using structured light sensor technology”. This project will be carried out in collaboration with our lab and the
Robots employ sensors and actuators that are subject to uncertainty. We learned last week how to quantify this uncertainty using probability density functions that associate a probability with each possible outcome of a random process, such as the reading of a sensor or the actual physical change of an actuator. One of the [...]
Review (pp. 270-275 of the book):
In general the position of a differential drive robot, like the E-Puck, is given by the vector
This position changes as the robot drives during each time step, . The incremental travel distances, or the change in the values of , are given by
,
,
,
,
[...]
The focus of WAFR is on the design and analysis of robot algorithms from both theoretical and practical angles. The topics of interest are very broad. We encourage papers on fundamental algorithmic issues, such as complexity, completeness, machine learning, probabilistic reasoning, and new programming paradigms, to name a few. We also encourage papers on applications [...]
Michael Otte has passed his PhD defense on “Any-Com Multi-Robot Path Planning” in front of
Prof. Nikolaus Correll (Chair)
Prof. Mike Mozer, Computer Science
Prof. Rick Han, Computer Science
Prof. Eric Frew, Aerospace
Prof. Jason Marden, Electrical Engineering
Prof. Gaurav Sukhatme (USC)
Prof. Richard Voyles (DU)
he is now [...]
Robots are systems that combine sensing, actuation, computation, and communication. Except for computation, all of its sub-systems are subject to a high degree of uncertainty. This can be observed in daily life: phone calls often are of poor quality, making it hard to understand the other party, characters are difficult to read from far away, [...]
Overview:
In the last lecture you examined different techniques for feature extraction and, in particular, line detection and fitting. Remember from the lecture that when we speak of a feature, such as a line, we are interested in information in sensor data that is robust to variations in rotation and scale as well as noise. [...]
The information generated by sensors can be large. For example, a simple webcam generates 640×480 color pixels (red, green and blue) or 921600 Bytes between 20-30 times per second. A single-ray laser scanner still provides around 600 distance measurements 10 times per second. This is in contrast to the information that the robot actually requires. [...]
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