This work describes an introductory multidisciplinary mechatronics/computer information systems laboratory course, Robotics with LEGO Mindstorms NXT, and a novel learning environment based on the DARPA Urban Challenge. The course is designed to employ project-based and discovery-based learning of robotics design and programming. A high profile engineering problem, DARPA Urban Challenge, was selected to motivate students. The challenge was modified to fit the LEGO Mindstorms robotic environment available for the course. Student-designed robots were to navigate streets of a miniature city. An easy configurable street-route consisting of modular route segments was developed and implemented. A Mini Urban Challenge competition was organized. The assessment metrics show high student satisfaction and exceeding of the learning objectives set for the course such as the increase in practical knowledge of basic robot controls, multisensor data fusion, and robot programming using a graphical robotic programming language.
Archives for December 2022
Exploring Alternatives to Wheeled Locomotion In Educational Robot Design
The use of mobile robotics as a platform for engineering education is well-established. It is unfortunate that mobile robotics as a discipline is mostly overlooked in undergraduate programs. The goal of most of the available pedagogy on mobile robotics is to act as a platform for teaching teamwork, basic engineering principles, programming, etc.[1,2] The experiments which are the subject of this paper take place in a senior-level elective on mobile robot design. It is worth emphasizing that the course teaches mobile robotics from a design and experimentation point of view, as a discipline in its own right. While the pedagogical goals of the course certainly involve reinforcement of the basic ABET criteria for undergraduate education, we believe that the most significant goal is to actually teach the students about mobile robotics in such a way that they would be able to design and build real systems for use in the real world[3]. This is especially interesting for students at the United States Naval Academy due to the increased emphasis on unmanned and autonomous technologies in military settings. In addition to studying wheeled and tracked vehicle design and control[4,5], exercises in the subject mobile robotics course focus on the use of articulated serial links for locomotion, including a wormlike robot and a multi-leg walking robot.
Pedagogical Approaches to Robot Motion Planning Instruction
Robot motion planning is a fairly intuitive and engaging topic, yet it is difficult to teach. The material is taught in undergraduate and graduate robotics classes in computer science, electrical engineering, mechanical engineering and aeronautical engineering, but at an abstract level. Deep learning could be achieved by having students implement and test different motion planning strategies. However, it is practically impossible in the context of a single class to have undergraduates implement motion planning algorithms that are powerful and fun to use, even when the students have proficient programming skills. Due to lack of supporting educational material, students are often asked to implement simple (and uninteresting) motion planning algorithms from scratch, or access thousands of lines of code and just figure out how things work. We present an ongoing project to develop microworld software and a modeling curriculum that supports undergraduate acquisition of motion planning knowledge and tool use by computer science and engineering students. The goal is to open the field of motion planning and robotics to young and enthusiastic talent.