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Why teach robotics using ROS ?

Michieletto S., Ghidoni S., Pagello E., Moro M., Menegatti E.

Journal of Automation Mobile Robotics and Intelligent Systems

2014

Vol. 8, No. 1

60--68

This paper focuses on the key role played by the adoption of a framework in teaching robotics with a computer science approach in the master in Computer Engineering. The framework adopted is the Robot Operating System (ROS), which is becoming a standard de facto inside the robotics community. The educational activities proposed in this paper are based on a constructionist approach. The Mindstorms NXT robot kit is adopted to trigger the learning challenge. The ROS framework is exploited to drive the students programming methodology during the laboratory activities and to allow students to exercise with the major computer programming paradigms and the best programming practices. The major robotics topics students are involved with are: acquiring data from sensors, connecting sensors to the robot, and navigate the robot to reach the final goal. The positive effects given by this approach are highlighted in this paper by comparing the work recently produced by students with the work produced in the previous years in which ROS was not yet adopted and many different software tools and languages were used. The results of a questionnaire are reported showing that we achieved the didactical objectives we expected as instructors.

Calibration of a rorating 2D laser range - finder using point - plane coistraints

Wai Yan So E., Basso F., Menegatti E.

Journal of Automation Mobile Robotics and Intelligent Systems

2013

Vol. 7, No. 2

30--38

A common method used to obtain 3D range data with a 2D laser range finder is to rotate the sensor. To combine the 2D range data obtained at different rotation angles into a common 3D coordinate frame, the axis of rotation relative to the mirror center of the laser range finder should be known. This axis of rotation is a line in 3D space with four degrees of freedom. This paper describes a method for recovering the parameters of this rotational axis, as well as the extrinsic calibration between the rota tional axis and a camera. It simply requires scanning several planar checkerboard patterns that are also imaged by a static camera. In particular, we use only correspondences between lines in the laser scans and planes in the camera images, which can be established easily even for non-visible lasers. Furthermore, we show that such line-on-plane correspondences can be modelled as pointplane constraints, a problem studied in the field of robot kinematics. We use a numerical solution developed for such point-plane constraint problems to obtain an initial estimate, which is then refined by a nonlinear minimiza- tion that minimizes the ,,line-of-sight" errors in the laser scans and the reprojection errors in the camera image. To validate our proposed method, we give experimental results using a LMS-100 mounted on a pan-tilt device in a nodding configuration.