Conference proceeding
Humanoid Throws Inaugural Pitch at Major League Baseball Game: Challenges, Approach, Implementation and Lessons Learned
2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAL)
01 Jan 2012
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Three different approaches of having a full-size humanoid throw the first pitch at a Major League Baseball game are tested and implemented. The approaches include kinematic mapping using a motion capture system to capture a human's throwing motion then mapping that to a full-size humanoid. The second method is a fully automated approach that uses the sparse reachable map to provide viable full body throwing trajectories to provide the end effector with the desired velocity. The third approach borrows from the animation industry. The key-frames of the desired trajectory are constructed by hand. The time between each key-frame is defined by the user. Interpolation methods are used to smoothly move between key frames while limiting the jerk. Each method is analyzed and tested in simulation and on physical hardware. The full-size humanoid used is the Hubo series robot. Based on the latter tests one method was chosen to successfully throw the ceremonial first pitch at a Major League Baseball game in April 2012.
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Details
- Title
- Humanoid Throws Inaugural Pitch at Major League Baseball Game: Challenges, Approach, Implementation and Lessons Learned
- Creators
- Daniel M. Lofaro - Drexel Univ, Elect & Comp Engn Dept, Philadelphia, PA 19104 USAPaul Oh - Drexel UniversityIEEE
- Publication Details
- 2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAL)
- Conference
- 2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAL), 9th
- Publisher
- IEEE
- Number of pages
- 5
- Grant note
- U. S. National Science Foundation (NSF); National Science Foundation (NSF) 0730206 / International Research and Education CNS- 0960061 / Major Research Infrastructure Recovery and Reinvestment (MIRR)
- Resource Type
- Conference proceeding
- Language
- English
- Identifiers
- 991019348759704721
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- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- Robotics