"Investigation of Cooperative SLAM For Low Cost Indoor Robots", Master Thesis presentation

Welcome to a presentation by Jafar Quetteineh about his Masters thesis "Investigation of Cooperative SLAM For Low Cost Indoor Robots".


In robotics, SLAM is the problem of dynamically building a map while simultaneously using it to localize the robot. Most SLAM solutions rely on laser ranger devices or vision sensors (cameras). This work studies the possibility of extending current established SLAM solutions to low cost robotic platforms with few low quality short range distance sensors (Infrared and Sonar) and weak odometry information.This work starts by studying the performance of a low cost robotic platform `DiddyBorg' and build models for sensors and odometry to be used in SLAM implementation. Next, three SLAM solutions are implemented, tested and compared both in real environment and under simulation.  The first two solutions are based on the well established EKF-SLAM and RBPF-SLAM while the third is a custom simplified solution that is proposed in this work.The results show that multi-hypothises based SLAM solutions are more likely to converge than single-hypothises (EKF) based solution. The results also shows that while the sparsity of the sensors is a limiting factor on SLAM quality, the limited range of the sensors is a determinant factor on the overall convergence of SLAM. Finally, a simple map coding and merging algorithm is presented for evaluation of multi-robot collaborative SLAM, the solution enables a group of robots to collaborate on the SLAM tasks without any priori knowledge of the relative locations of robots.

Monday, September 14, 2015, 14:00
SICS Swedish ICT, room von Neumann
Isafjordsgatan 22
Anders Lindgren