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Published byDana Lindsey Modified over 9 years ago
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1 Motivation We wish to test different trajectories on the Stanford Test Track in order to gain insight into the effects of different trajectory parameters on climbing effectiveness, such as: –Foot velocity at impact –Detachment strategies –Velocity & acceleration during pull stroke A tool is needed for trajectory generation, allowing for fast, simple iteration and effective control of trajectory. Stanford Test Track
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2 Requirements Provide a mechanism for user to specify a trajectory in an intuitive way. Provide visual feedback of actual 3-D trajectory. Using inverse kinematics, generate the necessary outputs to run this trajectory on hardware. –Stanford Test Track (motors controlling crank and wing angle) –RiSE platform (motors feeding into differential)
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3 Overall Procedure Initial Trajectory Inputs Possible Input Methods: 1.Beta Based Input 2.Time Based Input Matlab Preprocessor Output to Test Track or RiSE Visual Feedback of Actual 3D Trajectory
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4 Test Track 3D Trajectory Crank Angle Wing Angle Toe Position Touching wall Lifted from wall =0 – Arc length along 2-D trajectory - Wing Angle – Crank Angle Climbing direction
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5 (Crank Angle) Vs (arc length on Foot trajectory) (0 ~ 1) t t . . Moving forward Foot trajectory Mapping between and
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6 Defining phases based on * * * * Stroke Disengagement Swing ~0.85 ~0.4 Engagement Climbing direction stroke engagementdisengagement swing .
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7 Input Method 1 (Beta Based) User specified d dt) vs and vs Current system we are using Specify desired number and location of input points Approximate functions using Fourier Series Advantage: Intuitive way of specifying point velocity ( ) and wing angle ( ) at a specific toe position ( ) Disadvantage: Difficult to define input values at a specific time (t) – Arc length along 2-D trajectory - Wing Angle – Crank Angle.. Foot Contact: Foot Detachment: Foot Contact Foot Detachment
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8 Input Method 2 (Time Based) User specified vs t and vs t 4 phases - quintic splines (matched end conditions) Advantages: Exact Trajectory with explicit constraints on maximum and Control over accelerations in task coordinates Disadvantage: Difficult to define parameters at a specific toe position ( )... – Arc length along 2-D trajectory - Wing Angle – Crank Angle
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9 Mapping Procedure of Current System ( library of Matlab functions ) – Arc length along 2-D trajectory - Wing Angle – Crank Angle Initial Inputs Test Track OutputRiSE Output Configuration File User Inputs Link lengths Gear ratios of differential
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10 Summary Matlab preprocessor –Allows for testing different leg trajectories to find better trajectory for climbing Input: d dt) vs and vs Mapping Method –Fourier Curve Fit –Inverse Kinematics –Interpolation Output –Test Track input: vs t and vs t –RiSE input: 1 vs t and 2 vs t – Arc length along 2-D trajectory – Wing Angle – Crank Angle – Rotation angle of Motor 1 2 – Rotation angle of Motor 2.
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