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A Multidisciplinary Approach for Using Robotics in Engineering Education

A Multidisciplinary Approach for Using Robotics in Engineering Education. Jerry Weinberg Gary Mayer Department of Computer Science Southern Illinois University Edwardsville. The integrated systems nature of robotics make robot projects an interesting and useful teaching tool

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A Multidisciplinary Approach for Using Robotics in Engineering Education

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  1. A Multidisciplinary Approach for Using Robotics in Engineering Education Jerry Weinberg Gary Mayer Department of Computer Science Southern Illinois University Edwardsville

  2. The integrated systems nature of robotics make robot projects an interesting and useful teaching tool • Electrical Components • Mechanical Components • Computational Components • The integrated systems nature of robotics make robot projects for many small and medium institutions difficult • Cost of pre-fabricated robots • Full range of expertise needed for constructing and teaching

  3. Robot Platforms are becoming inexpensive, accessible, and stable • Cost of pre-fabricated robots prohibitive • Increase the “Threshold of Indignation” • Effort we are willing to put forth to get a task done (Saffo) • Easier, familiar mechanical components • Plug & Play feel to sensors • Wide range of programming environments • Stability reduces overhead of support, malignance, and troubleshoot

  4. Teaching still requires a broader range of knowledge • Or de-emphasis of some areas • Robotics Multidisciplinary Action Group • Faculty from ECE, ME, IE, and CS • Cross-Functional team for designing course material • Share expertise through sharing of course modules and graduate assistants • Course modules provide a vocabulary • Design discussions take course modules and previous student work and adapt them to make assignment that are accessible to students in other areas

  5. Area: Course Concepts Emphasized Concepts Shared Computer Science: Artificial Intelligence Embedded agents, deliberative/reactive robot control, planning, multitasking Subsumption architecture, search strategies, multitasking, cross compiling, multiplexing Mechanical Engineering: Mechatronics Robotics – dynamics & control Sensor processing, logic circuits, real-time processing, actuators, analog/digital conversion, kinematics, trajectory planning Differential motion, gearing, translation motion Industrial Engineering: Engineering Problem Solving Problem formulation, structural design, algorithmic design, search strategies, gearing, drive train Problem analysis and definition, integrated system design Electrical & Computer Engineering: Senior Project Signal processing, robotic system design, and project management, analog/digital conversion Signal processing, Sensor characteristics, robotic system integration

  6. Multidisciplinary Approach: • Overcome need for broad expertise through sharing of knowledge • Take advantage of cross-cutting funding programs • Near Future Goal: Multidisciplinary Engineering Design / Robotics Course • Cross-Functional student teams • Meet ABET requirements

  7. Push on the abilities of inexpensive platforms to teach more advanced concepts • Navigation and Planning • Handy Board: lower threshold of indignation • Exploring board design for more Plug and Play feel • RCX: limitations of sensors and firmware • Exploring ways to go beyond Behavior-Based Control

  8. Current Project • Purpose: • Develop complex behaviors on an inexpensive platform • Approach: • Emulate behavior that could be modeled in both a reactive and deliberative system • Task: • Forage • Search, obstacle avoidance, path planning, and navigation

  9. Design • LEGO Mindstorms RCX • Not-Quite-C (NQC) • “Backpack” • Dual-differential drive • Lit-target capture • Obstacle avoidance • IR communication • Compass sensor • Two rotation sensors • Distance and turning

  10. Reactive-Based Reasoning(ascending order of precedence) • Forage (default) – random search routine • Acquire – captures target using light sensor • Return – directs robot back to starting location using IR messaging • “Marco Polo” • Release – releases target and resets system to look for next target • Avoid – obstacle avoidance routine

  11. Deliberative-Based Approach • Forage (default) – planned search routine using provided map of arena • Acquire – captures target using light sensor • Return – directs robot back to starting location using compass and rotation sensors • Release – releases target and resets system to look for next target • Avoid – obstacle avoidance routine

  12. Challenges • Mechanical • Drift • Battery power and drain • Limited sensor ports • Sensor limitations • Software • Encoding environment • Hardware interface

  13. Options to Explore • Dual-RCX (Master / Slave) • Increased sensor ports, memory, and processing • Triangulation • Multiple stationary RCXs • Mobile sensors for multi-use • Ex: Light and gear box combo allowing sensor to track ground lines, light levels ahead, and overhead light levels.

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