Presentation on theme: "Just Add Wheels: Leveraging Commodity Laptop Hardware for Robotics Education Jonathan Kelly, Jonathan Binney, Arvind Pereira, Omair Khan and Gaurav S."— Presentation transcript:
Just Add Wheels: Leveraging Commodity Laptop Hardware for Robotics Education Jonathan Kelly, Jonathan Binney, Arvind Pereira, Omair Khan and Gaurav S. Sukhatme Robotic Embedded Systems Laboratory Department of Computer Science University of Southern California Sunday, July 13, 2008
/16USC Robotic Embedded Systems Lab 2 Introduction We propose using commodity laptop hardware for robotics education. We motivate the approach by discussing relevant studies and statistics. We then describe our prototype laptop robot, including software based on the open source Player-Stage package. We present results from monocular SLAM and bump detection experiments, using laptop sensors.
/16USC Robotic Embedded Systems Lab Talk Outline Introduction Motivation Leveraging Laptop Hardware for Education The LapBot, a Prototype Laptop Robot Monocular SLAM Bump Sensing Conclusions and Future Work 3
/16USC Robotic Embedded Systems Lab Motivation Robotics projects are fun and exciting – excellent for learning about physics, math, computer science etc. Can be used to motivate students who may not otherwise choose to pursue Science or Engineering (Blank 2006). Numerous barriers to widespread adoption of robotics curriculum, however, at both college and K-12 levels. Include lack of teacher training, suitable educational resources, and affordable robot platforms (Mataric et al. 2007). 4
/16USC Robotic Embedded Systems Lab Leveraging Laptop Hardware How can we both interest students in robotics, and get them involved at reasonably low cost? Need mobility, sensor and software components. Idea: Leverage sensors and computing power inside the laptops that they already own. 2007 ECAR survey: 73.7% of college students now own laptops. Cameras already available in many models, accelerometers on some (Acer, Apple, IBM). 5
/16USC Robotic Embedded Systems Lab Our Approach 1.Explore the idea of using student-owned laptops as capable robot platforms. 2.Use on-board hardware (e.g. camera, accelerometer etc.) for sensing and computing. 3.Just add wheels, i.e. a motorized base, for mobility. 4.Develop an open source software platform, freely available, to take advantage of this hardware. 6
/16USC Robotic Embedded Systems Lab The LapBot Prototype hardware / software platform. Apple MacBook Core Duo laptop iRobot Create mobile base Runs (free) Ubuntu Linux. Software for two tasks: Monocular SLAM using the built-in iSight camera. Bump sensing / obstacle detection using accelerometer. 7
/16USC Robotic Embedded Systems Lab System Block Diagram 8
/16USC Robotic Embedded Systems Lab MonoSLAM We use a freely-available monocular (single- camera) SLAM package (Davison 2003). Full 6-DoF SLAM running in real time. Requires initialization using known calibration target. Image data is acquired from internal iSight camera. Grabs frames on the MacBook Core Duo at 5 – 10 Hz. 640 x 480 VGA resolution. Works qualitatively very well. 9
/16USC Robotic Embedded Systems Lab MonoSLAM Example 10
/16USC Robotic Embedded Systems Lab Bump Sensing 11 Access the on-board Apple Sudden Motion Sensor. High-resolution, high-speed three-axis solid-state accelerometer unit. 250 counts per gravity. Sampled at more than 300 Hz. No official API from Apple (yet), but reading data is easy. Repurpose the sensor for bump/collision detection. Threshold test on smoothed sensor output. > 0.4 gs is a considered a bump. Currently, robot emits an auditory tone when bumped.
/16USC Robotic Embedded Systems Lab Bump Sensing Example 12
/16USC Robotic Embedded Systems Lab The LapBot in Action Video shows student driving the LapBot manually in our lab building. Display support holds screen (and camera) rigidly upright – this aides feature tracking. 13
/16USC Robotic Embedded Systems Lab Conclusions Described and motivated the design of a prototype laptop robot built to leverage hardware that is likely available (or will be available) to students. Both MonoSLAM and accelerometer-based bump sensing work well, and run in real-time on laptop processor. One of the benefits of using a full laptop instead of an embedded processor. Emphasize that all hardware except for locomotion is built into the laptop itself. 14
/16USC Robotic Embedded Systems Lab Future Work Continuing to develop out-of-the-box software packages for a variety of laptop hardware. User should be able to install with minimal effort, i.e. the package has to just work. Trial in a classroom environment. Presently, we have a simple proof-of-concept implementation. Need to carefully evaluate the feasibility of the approach for a real classroom. Ideally, this would be a freshman college class. K-12 would come later. 15
/16USC Robotic Embedded Systems Lab 16 Thank You. Questions?