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Innovative Humanoid Robotics for Human Environment Manipulation at MIT CSAIL

The MIT CSAIL Humanoid Robotics Group is advancing manipulation technologies in human environments with the Domo robot, featuring 29 degrees of freedom in its elastic actuator arms, hands, and neck. Designed to collaborate with humans, Domo excels in tasks such as carrying groceries, aiding in household chores, and cooperative manufacturing. The robot utilizes active vision and sensory feedback to adapt to its surroundings and simplify interaction with everyday objects, ultimately enhancing our physical abilities and redefining collaborative manipulation in daily life.

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Innovative Humanoid Robotics for Human Environment Manipulation at MIT CSAIL

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  1. Aaron Edsinger & Charlie Kemp Humanoid Robotics Group MIT CSAIL Manipulation in Human Environments

  2. Domo • 29 DOF • 6 DOF Series Elastic Actuator (SEA) arms • 4 DOF SEA hands • 2 DOF SEA neck • Active vision head • Stereo cameras • Gyroscope • Sense joint angle + torque • 15 node Linux cluster

  3. Manipulation in Human Environments Human environments are designed to match our cognitive and physical abilities • Work with everyday objects • Collaborate with people • Perform useful tasks

  4. Applications • Aging in place • Cooperative manufacturing • Household chores

  5. Three Themes • Let the body do the thinking • Collaborative manipulation • Task relevant features

  6. Let the Body do the Thinking • Design • Passive compliance • Force control • Human morphology

  7. Let the Body do the Thinking • Compensatory behaviors • Reduce uncertainty • Modulate arm stiffness • Aid perception (motion, visibility) • Test assumptions (explore)

  8. Let the Body Do the Thinking

  9. Collaborative Manipulation • Complementary actions • Person can simplify perception and action for the robot • Robot can provide intuitive cues for the human • Requires matching to our social interface

  10. Collaborative Manipulation Social amplification

  11. Collaborative Manipulation • A third arm: • Hold a flashlight • Fixture a part • Extend our physical abilities: • Carry groceries • Open a jar • Expand our workspace: • Place dishes in a cabinet • Hand a tool • Reach a shelf

  12. Task Relevant Features • What is important? • What is irrelevant? *Distinct from object detection/recognition.

  13. Structure In Human Environments Donald Norman The Design of Everyday Objects

  14. Structure In Human Environments Human environments are constrained to match our cognitive and physical abilities • Sense from above • Flat surfaces • Objects for human hands • Objects for use by humans

  15. Why are tool tips common? • Single, localized interface to the world • Physical isolation helps avoid irrelevant contact • Helps perception • Helps control

  16. Tool Tip Detection • Visual + motor detection method • Kinematic Estimate • Visual Model

  17. Mean Pixel Error for Automatic and Hand Labelled Tip Detection

  18. Mean Pixel Error for Hand Labeled, Multi-Scale Detector, and Point Detector

  19. Model-Free Insertion • Active tip perception • Arm stiffness modulation • Human interaction

  20. Other Examples • Circular openings • Handles • Contact Surfaces • Gravity Alignment

  21. Future:Generalize What You've Learned • Across objects • Perceptually map tasks across objects • Key features map to key features • Across manipulators • Motor equivalence • Manipulator details may be irrelevant

  22. RSS 2006 Workshop Manipulation for Human Environments Robotics: Science and Systems University of Pennsylvania , August 19th, 2006 manipulation.csail.mit.edu/rss06

  23. Summary • Importance of Task Relevant Features • Example of the tool tip • Large set of hand tools • Robust detection (visual + motor) • Kinematic estimate • Visual model

  24. In Progress • Perform a variety of tasks • Insertion • Pouring • Brushing

  25. Learning from Demonstration

  26. The Detector Responds To Fast Motion Convex

  27. Multi-scale Histogram (Medial-Axis, Hough Transform for Circles) Motion Weighted Edge Map Video from Eye Camera Local Maxima

  28. Defining Characteristics • Geometric • Isolated • Distal • Localized • Convex • Cultural/Design • Far from natural grasp location • Long distance relative to hand size

  29. Other Task Relevant Features?

  30. Detecting the Tip

  31. Include Scale and Convexity

  32. Distinct Perceptual Problem • Not object recognition • How should it be used • Distinct methods and features

  33. Use The Hand's Frame • Combine weak evidence • Rigidly grasped

  34. Acquire a Visual Model

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