1. [Publications](/publications)
2. HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers
 
 # HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers

  ![](/sites/default/files/styles/wide/public/publications/0397.jpg?itok=SMYdBLlt)

 We introduce a new simulation benchmark "HandoverSim" for human-to-robot object handovers. To simulate the giver's motion, we leverage a recent motion capture dataset of hand grasping of objects. We create training and evaluation environments for the receiver with standardized protocols and metrics. We analyze the performance of a set of baselines and show a correlation with a real-world evaluation.



 ## Authors



[Yu-Wei Chao](/person/yu-wei-chao)

Chris Paxton (NVIDIA)

Yu Xiang (UT Dallas)

[Wei Yang](/person/wei-yang)

[Balakumar Sundaralingam](/person/balakumar-sundaralingam)

Tao Chen (MIT)

[Adithya Murali](/person/adithya-murali)

Maya Cakmak (University of Washington)

Dieter Fox (NVIDIA)

 

 

 ## Publication Date



Monday, May 23, 2022

 

 ## Published in



[IEEE International Conference on Robotics and Automation (ICRA) 2022](https://www.icra2022.org)

 

 ## Research Area



[Computer Vision](/research-area/computer-vision)

[Robotics](/research-area/robotics)

 

 

 ## External Links



[Paper, Code, Video](https://handover-sim.github.io)

 

 

 ## Copyright



This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to <pubs-permissions@ieee.org>.