China Talks Robot

Slide1: 

Kevin L. Moore, Ph.D., P.E.¹ G.A. Dobelman Distinguished Chair and Professor of Engineering Division of Engineering Colorado School of Mines ¹Some work performed at the Johns Hopkins University Applied Physics Laboratory and the Utah State University Center for Self- Organizing and Intelligent Systems Dynamic Resource Networks: Coordination and Control of Networks with Mobile Actuators and Sensors presented at Xi'an Jiao Tong  University

Outline: 

Outline Background and Research Foci Intelligent Control Single-Entity Autonomy Cooperative Autonomy

Slide3: 

Kevin L. Moore, Ph.D., P.E.¹ G.A. Dobelman Distinguished Chair and Professor of Engineering Division of Engineering Colorado School of Mines ¹Some work performed at the Johns Hopkins University Applied Physics Laboratory and the Utah State University Center for Self- Organizing and Intelligent Systems Intelligent Behavior Generation for Autonomous Mobile Robots: Control, Planning, and Coordination presented at Beijing Institute of Technology

Outline: 

Outline Background and Research Foci Intelligent Control Single-Entity Autonomy Cooperative Autonomy

Slide5: 

Colorado School of Mines Located in Golden, Colorado, USA 10 miles West of Denver CSM has about 300 faculty and 4000 students CSM is a public research institution devoted to engineering and applied science, especially: Discovery and recovery of resources Conversion of resources to materials and energy Utilization in advanced processes and products Economic and social systems necessary to ensure prudent and provident use of resources in a sustainable global society CSM sits in the foothills of the Rocky Mountains

Background About Me: 

Background About Me Joined CSM August 2005 Spent a year at Johns Hopkins Applied Physics Lab (sabbatical) Independent researcher, focusing on autonomous systems and control Previously spent 15 years in Academia 6 years at Utah State Research in the area of control systems and robotics Teaching focus on junior/senior/capstone design experiences Director of the Center for Self-Organizing and Intelligent Systems 9 years at Idaho State Research in the area of control systems, especially for materials processing Founding director of Measurement and Control Eng. Research Center Served a one-year stint as Interim Associate Dean Prior to that PhD in EE (controls) from Texas A&M, while working as a lecturer 3 years at Hughes Aircraft MSEE degree from USC in LA BSEE degree from LSU in Baton Rouge Internship at Texas Instruments in Houston

Research Foci: 

Research Foci Iterative Learning Control

Slide8: 

Iterative Learning Control –Systems that Do the Same Thing Over and Over Step 1: Robot at rest, waiting for workpiece. Step 3: Robot moves to desired location and executes its task. Step 2: Workpiece moved into position. Step 4: Robot returns to rest and waits for next workpiece.

Errors are Repeated WhenTrajectories are Repeated : 

Errors are Repeated When Trajectories are Repeated A typical joint angle trajectory for the example might look like this: Each time the system is operated it will see the same overshoot, rise time, settling time, and steady-state error. Iterative learning control attempts to improve the transient response by adjusting the input to the plant during future system operation based on the errors observed during past operation.

Slide10: 

Iterative Learning Control

An ILC Example: 

An ILC Example Laser Pointer Camera Target Path Image Capture ILC Algorithm Motor Control (two computers)

Gimbal Motion Trial 1: 

Gimbal Motion Trial 1 Gimbal Motion Trial 4

Research Foci: 

Research Foci Iterative Learning Control Control of Materials Processing Foundry Cupola Alumina Primary Production Gas Metal Arc Welding

Cupola Control Project: 

Cupola Control Project Cupola Furnace: Charged with coke, metal, and other materials Hot air blast with oxygen added Diameters from 2’ to 15’, melt rates from 1 to 200 tons per hour An essential part of most cast iron foundries Project Goal: Develop intelligent control of meltrate, temperature, and carbon composition Develop less reliance on operator experience and develop tools for automatic control

Welding Research: 

Welding Research Goal: achieve a “good” weld by controlling Torch travel speed Electrode wire speed Torch height Power supply Research led to a book

Research Foci: 

Research Foci Iterative Learning Control Control of Materials Processing Foundry Cupola Alumina Primary Production Gas Metal Arc Welding Robotics and Autonomous Systems Autonomous Mobile Robots “Build from scratch” Retro-fit – autonomous farming applications UAV applications

USU-Developed Robot Family: 

USU-Developed Robot Family

ODIS in Theatre: 

ODIS in Theatre 23 ODIS-T2 robots in Theaters since March 2004 Additional robots in production Stand-off is the main benefit

Bigger Vehicles: 

Bigger Vehicles

Research Foci: 

Research Foci Iterative Learning Control Control of Materials Processing Foundry Cupola Alumina Primary Production Gas Metal Arc Welding Robotics and Autonomous Systems Autonomous Mobile Robots “Build from scratch” Retro-fit – autonomous farming applications UAV applications Mobile Sensor/Actuator Networks Networks

Slide22: 

Mote-Based Distributed Robots Prototype plume-tracking testbed - 2004 2nd Place Prize 2005 Crossbow Smart-Dust Challenge

Research Foci: 

Research Foci Iterative Learning Control Control of Materials Processing Foundry Cupola Alumina Primary Production Gas Metal Arc Welding Robotics and Autonomous Systems Autonomous Mobile Robots “Build from scratch” Retro-fit – autonomous farming applications UAV applications Mobile Sensor/Actuator Networks Networks Control, “Intelligent” Control “Intelligent” Control Single-Entity Autonomy Cooperative Autonomy

Outline: 

Outline Background and Research Foci Intelligent Control Single-Entity Autonomy Cooperative Autonomy

Slide25: 

Comments on “Intelligent” Control

Slide26: 

Intelligent Behavior Generation for Single-Entity Autonomy – Work Performed at Utah State University – – Center for Self-Organizing and Intelligent Systems –

Slide27: 

Intelligent Behavior Generation for Cooperative Autonomy – Work Performed at Johns Hopkins University – – Applied Physics Laboratory –