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| CSE 190 Computational Robotics | 1 | 1 | CSE 190 Computational Robotics | |
| PA2: Mobile Robot Localization using Particle Filter Method | 2 | 2 | PA2: Mobile Robot Localization using Particle Filter Method | |
| 3 | 3 | |||
| Objective | 4 | 4 | Objective | |
| You will learn about the methods for estimating the unknown pose of a moving robot, inside an environment whose map is known, by global localization using the particle filter method. A reliable position estimation is of fundamental importance to building truly autonomous robots, especially the ones that perform navigation and local manipulation tasks, within indoor environments. | 5 | 5 | You will learn about the methods for estimating the unknown pose of a moving robot, inside an environment whose map is known, by global localization using the particle filter method. A reliable position estimation is of fundamental importance to building truly autonomous robots, especially the ones that perform navigation and local manipulation tasks, within indoor environments. | |
| 6 | 6 | |||
| Task | 7 | 7 | Task | |
| Implement a particle filter in ROS for localizing a robot in the Stage world without knowing its starting pose, using Laser sensor measurements from the stage simulator. Play with the number of particles, motion models, measurement models, and resampling algorithms to achieve a better metric for localization in terms of accuracy and speed. | 8 | 8 | Implement a particle filter in ROS for localizing a robot in the Stage world without knowing its starting pose, using Laser sensor measurements from the stage simulator. Play with the number of particles, motion models, measurement models, and resampling algorithms to achieve a better metric for localization in terms of accuracy and speed. | |
| 9 | 9 | |||
| Important dates: | 10 | |||
| Final submission deadline: Thursday May 5, 11:59 PM | 11 | |||
| Required solution: robot.py (submit the code in python for this assignment) | 12 | 10 | Required solution: robot.py (submit the code in python for this assignment) | |
| Acquiring the starter code: The skeleton code is available at this git repo: https://git.ucsd.edu/srsivara/cse_190_pa2. Clone the repository into your catkin_ws/src directory and then build it like a normal ros package. | 13 | 11 | Acquiring the starter code: The skeleton code is available at this git repo: https://git.ucsd.edu/srsivara/cse_190_pa2. Clone the repository into your catkin_ws/src directory and then build it like a normal ros package. |