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Picture of Terminator

Picture of Terminator. Introduction to Robotics (ES159) Advanced Introduction to Robotics (ES259) S pring 2007 Robert Wood 149 Maxwell Dworkin rjwood@eecs.harvard.edu www.eecs.harvard.edu/~rjwood. Personnel . Instructor: Me TFs: Shelton Yuen Dr. Benjamin Pierce. Primary:

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  1. Picture of Terminator

  2. Introduction to Robotics (ES159)Advanced Introduction to Robotics (ES259)Spring 2007Robert Wood149 Maxwell Dworkinrjwood@eecs.harvard.eduwww.eecs.harvard.edu/~rjwood ES159/ES259

  3. Personnel • Instructor: • Me • TFs: • Shelton Yuen • Dr. Benjamin Pierce ES159/ES259

  4. Primary: M. Spong, S. Hutchinson, and M. Vidyasagar, “Robot Modeling and Control”, Wiley Texts Secondary: Li, Murray, Sastry, “A Mathematical Introduction to Robotic Manipulation”, CRC Press ES159/ES259

  5. Lab • Multiple experiments with a 6-axis industrial robotic arm (RRR) • Forward/inverse kinematics • Velocity kinematics • Control • Path planning • Manipulation • Equipment: • Open architecture industrial arm from CRS (Catalyst-5), retrofitted by Quanser with a Matlab interface • Will require extensive use of Matlab/Simulink ES159/ES259

  6. Problem sets and exams • Problem sets: approximately every other week, due two weeks afterwards • Will often include Matlab/Simulink problems • Matlab review session(s)? • No midterm, one comprehensive final exam ES159/ES259

  7. Final projects • Required for graduate students • Bonus for undergraduates • Can involve any field of robotics • I will be happy to suggest topics • I strongly encourage you to incorporate your research into the project (or the final project into your research!) • You will have access to the following facilities: • The 159 lab arm • Machine shop • All resources in the Harvard Microrobotics Lab ES159/ES259

  8. Course outline • First 2/3: traditional analysis of robotic manipulators • Homogeneous transforms • Forward/inverse kinematics • Velocity kinematics, dynamics • Motion planning • Control • Final 1/3: introduction to special topics • Sensors and actuators • Mobile agents, SLAM • Computer vision • MEMS, microrobotics • Surgical robotics, teleoperation • Biomimetic systems Labs will follow along with these topics Active research areas, potential subjects for final projects ES159/ES259

  9. Introduction • Historical perspective • The acclaimed Czech playwright Karel Capek (1890-1938) made the first use of the word ‘robot’, from the Czech word for forced labor or serf. • The use of the word Robot was introduced into his play R.U.R. (Rossum's Universal Robots) which opened in Prague in January 1921. In R.U.R., Capek poses a paradise, where the machines initially bring so many benefits but in the end bring an equal amount of blight in the form of unemployment and social unrest. • Science fiction • Asimov, among others glorified the term ‘robotics’, particularly in I, Robot, and early films such as Metropolis (1927) paired robots with a dystopic society • Formal definition (Robot Institute of America): • "A reprogrammable, multifunctional manipulator designed to move material, parts, tools, or specialized devices through various programmed motions for the performance of a variety of tasks". ES159/ES259

  10. 100s of movies Chances are, something you eat, wear, or was made by a robot 01_02 Robots in everyday use and popular culture http://www.robotuprising.com/ Roomba: $142M in sales for 2005 ES159/ES259

  11. Common applications Picture of Roomba • Industrial • Robotic assembly • Commercial • Household chores • Military • Medical • Robot-assisted surgery ES159/ES259

  12. JHUROV; Johns Hopkins Common applications • Planetary Exploration • Fast, Cheap, and Out of Control • Mars rover • Undersea exploration ES159/ES259

  13. 01_01 Industrial robots • High precision and repetitive tasks • Pick and place, painting, etc • Hazardous environments ES159/ES259

  14. 01_03 Representations • For the majority of this class, we will consider robotic manipulators as open or closed chains of links and joints • Two types of joints: revolute (q) and prismatic (d) ES159/ES259

  15. Definitions • End-effector/Tool • Device that is in direct contact with the environment. Usually very task-specific • Configuration • Complete specification of every point on a manipulator • set of all possible configurations is the configuration space • For rigid links, it is sufficient to specify the configuration space by the joint angles • State space • Current configuration (joint positions q) and velocities • Work space • The reachable space the tool can achieve • Reachable workspace • Dextrous workspace ES159/ES259

  16. 01_06 Common configurations: wrists • Many manipulators will be a sequential chain of links and joints forming the ‘arm’ with multiple DOFs concentrated at the ‘wrist’ ES159/ES259

  17. Utah MIT hand 01_07 Example end-effector: Grippers • Anthropomorphic or task-specific • Force control v. position control ES159/ES259

  18. 01_09 Common configurations: elbow manipulator • Anthropomorphic arm: ABB IRB1400 • Very similar to the lab arm (RRR) ES159/ES259

  19. 01_10 Workspace: elbow manipulator ES159/ES259

  20. 01_12 Common configurations: Stanford arm (RRP) • Spherical manipulator (workspace forms a set of concentric spheres) ES159/ES259

  21. Adept Cobra Smart600 SCARA robot 01_14 Common configurations: SCARA (RRP) ES159/ES259

  22. Seiko RT3300 Robot 01_15 Common configurations: cylindrical robot (RPP) • workspace forms a cylinder ES159/ES259

  23. 01_16 Common configurations: Cartesian robot (PPP) • Increased structural rigidity, higher precision • Pick and place operations ES159/ES259

  24. 01_17 Workspace comparison (a) spherical (b) SCARA (c) cylindrical (d) Cartesian ES159/ES259

  25. ABB IRB940 Tricept 6DOF Stewart platform ABB IRB6400 01_18 Parallel manipulators • some of the links will form a closed chain with ground • Advantages: • Motors can be proximal: less powerful, higher bandwidth, easier to control • Disadvantages: • Generally less motion, kinematics can be challenging ES159/ES259

  26. Simple example: control of a 2DOF planar manipulator 01_19 • Move from ‘home’ position and follow the path AB with a constant contact force F all using visual feedback ES159/ES259

  27. 0 1 2 0 1 2 01_20 Coordinate frames & forward kinematics • Three coordinate frames: • Positions: • Orientation of the tool frame: ES159/ES259

  28. 01_21 Inverse kinematics • Find the joint angles for a desired tool position • Two solutions!: elbow up and elbow down ES159/ES259

  29. State space includes velocity Inverse of Jacobian gives the joint velocities: This inverse does not exist when q2 = 0 or p, called singular configuration or singularity 01_23 Velocity kinematics: the Jacobian ES159/ES259

  30. 01_24 Path planning • In general, move tool from position A to position B while avoiding singularities and collisions • This generates a path in the work space which can be used to solve for joint angles as a function of time (usually polynomials) • Many methods: e.g. potential fields • Can apply to mobile agents or a manipulator configuration ES159/ES259

  31. desired trajectory controller error system dynamics measured trajectory (w/ sensor noise) actual trajectory 01_24 Joint control • Once a path is generated, we can create a desired tool path/velocity • Use inverse kinematics and Jacobian to create desired joint trajectories ES159/ES259

  32. Other control methods • Force control or impedance control (or a hybrid of both) • Requires force/torque sensor on the end-effector • Visual servoing • Using visual cues to attain local or global pose information • Common controller architectures: • PID • Adaptive • Repetitive • Challenges: • Underactuation • Nonholonomy (mobile agents) • nonlinearity ES159/ES259

  33. General multivariable control overview joint controllers motor dynamics manipulator dynamics desired joint torques state estimation sensors estimated configuration inverse kinematics, Jacobian desired trajectory ES159/ES259

  34. Sensors and actuators • sensors • Motor encoders (internal) • Inertial Measurement Units • Vision (external) • Contact and force sensors • motors/actuators • Electromagnetic • Pneumatic/hydraulic • electroactive • Electrostatic • Piezoelectric • Basic quantities for both: • Bandwidth • Dynamic range • sensitivity ES159/ES259

  35. Whegs; CWRU RHex; Michigan Mobile Agents and SLAM • For untethered and autonomous applications, the performance of a robotic system (P), whether defined by capability or robustness, can be related to an agent’s intelligence (I), mobility (M), and multiplicity (N): MicroBat; UCLA ES159/ES259

  36. Mobile Agents and SLAM • Monte Carlo localization • SLAM: ‘Simultaneous locomotion and Map-building’ ES159/ES259

  37. Computer Vision • Simplest form: estimating the position and orientation of yourself or object in your environment using visual cues • Usually a statistical process • Ex: finding lines using the Hough space • More complex: guessing what the object in your environment are • Biomimetic computer vision: how do animals accomplish these tasks: • Obstacle avoidance • Optical flow? • Object recognition • Template matching? ES159/ES259

  38. Donald; Dartmouth MEMS and Microrobotics • Difficult definition(s): • Robotic systems with feature sizes < 1mm • Robotic systems dominated by micro-scale physics • MEMS: Micro ElectroMechanical Systems • Modified IC processes to use ‘silicon as a mechanical material’ Fearing; Berkeley Pister; Berkeley ES159/ES259

  39. Surgical robotics • Minimally invasive surgery • Minimize trauma to the patient • Potentially increase surgeon’s capabilities • Force feedback necessary, tactile feedback desirable ES159/ES259

  40. BigDog; Boston Dynamics MFI; Harvard & Berkeley Ayers; Northeastern Biomimetic Robots • Using biological principles to reduce design space ES159/ES259

  41. Humanoid robots • For robots to efficiently interact with humans, should they be anthropomorphic? QRIO Sony Asimo; Honda ES159/ES259

  42. Next class… • Homogeneous transforms as the basis for forward and inverse kinematics • Come talk to me if you have questions or concerns! ES159/ES259

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