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Domo: Partner Robots for Manipulation Aaron Edsinger MIT Computer Science and Artificial Intelligence Laboratory Humanoid Robotics Group edsinger@csail.mit.edu. 1.26.2006. Robots That Can Work Alongside Humans. Built for human environments Safety in the human workspace
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Domo: Partner Robotsfor ManipulationAaron EdsingerMIT Computer Science and Artificial Intelligence LaboratoryHumanoid Robotics Groupedsinger@csail.mit.edu 1.26.2006
Robots That Can Work Alongside Humans • Built for human environments • Safety in the human workspace • Humanoid body to work with everyday objects • Perform tasks that are important to people using natural strategies with everyday objects
Robots That Can Work Alongside Humans • Human-robot interface: use the body, not the keyboard. • Apply human expertise: coach the robot, through physical, visual, and auditory guidance.
Robust Manipulation and Human Interactions in Unstructured Environments • Active Perception: Use the robot body to assist perception • Human Safety: Passive compliance and force control • Integration: Architecture to support rich, tightly coupled behaviors • Perceptual constraints: Focus resources on only task-relevant features of objects and interactions
29 active degrees of freedom (DOF) • Two 6 DOF force controlled arms using Series Elastic Actuators • Two 6 DOF force controlled hands using SEAs • A 2 DOF force controlled neck using SEAs • Stereo pair of Point Grey Firewire CCD cameras • Stereo Videre STH-DCSG-VAR-C Firewire cameras • Intersense 3 axis gyroscope • Two 4 DOF hands using Force Sensing Compliant (FSC) actuators Domo
Embedded brushless and brushed DC motor drivers • 5 Embedded Motorola 56F807 DSPs running a 1khz control loop • 4 CANBus channels providing 100hz communication to external computation. • 49 potentiometers, 7 encoders, 24 tactile sensors, 12 brushless amplifiers, 17 brushed amplifiers, 12 sensor conditioners embedded on-board • An estimated 500 fabricated mechanical components and 60 electronics PCBs • 15 node Debian Linux cluster running a mixture of C/C++/Python and utilizing the Yarp and pysense robot libraries. Domo
Series Elastic and Force Sensing Compliant Actuators • Mechanically simple • Improved stability • Shock tolerance • Highly backdrivable • Low-grade components • Low impedance at high frequencies
Passive and Active Compliance Series Elastic Actuator Force based grasping
Domo: Behavior Based Architecture • Architectural primitives allow tightly integrated system • 100hz scheduler • Dynamic arbitration • ~15 node Linux cluster • ~50 threads currently Homeostat
Architecture Example Arm Behaviors Head Behaviors
Behavior Based Architecture Arm Behaviors Head Behaviors
Detection of Human Interaction Forces Interaction forces at hands are approximately equal and opposite Interaction forces present Interaction forces not present
Detection of Human Interaction Forces Ballistic reaching: prediction error Efference copy model generates torque prediction. Torque prediction errors drive visual attention system. External forces: prediction error
Learning Tool Use By Demonstration • Motion feature points for tip detection • 3D position estimation using probabilistic model
Autonomous Detection and Control ofHuman Tools by Demonstration