Conference proceeding
Humanoid pitching at a Major League Baseball game: Challenges, approach, implementation and lessons learned
2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), pp 423-428
Nov 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.
Metrics
Details
- Title
- Humanoid pitching at a Major League Baseball game: Challenges, approach, implementation and lessons learned
- Creators
- Daniel M Lofaro - Drexel UniversityChunyang Sun - Nanyang Technological UniversityPaul Oh - Drexel UniversityIEEE
- Publication Details
- 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), pp 423-428
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Web of Science ID
- WOS:000392842100064
- Scopus ID
- 2-s2.0-84891054709
- Other Identifier
- 991019348753604721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Robotics