Litcius/Paper detail

HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers

Yu-Wei Chao, Chris Paxton, Xiang Yu, Wei Yang, Balakumar Sundaralingam, Tao Chen, Adithyavairavan Murali, Maya Çakmak, Dieter Fox

20222022 International Conference on Robotics and Automation (ICRA)27 citationsDOI

Abstract

We introduce a new simulation benchmark “Han-doverSim” 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. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> Code is open sourced at https://handover-sim.github.io.

Topics & Concepts

Benchmark (surveying)Computer scienceHandoverLeverage (statistics)Code (set theory)Set (abstract data type)RobotArtificial intelligenceObject (grammar)Programming languageComputer networkGeographyGeodesyRobot Manipulation and LearningHand Gesture Recognition SystemsMultimodal Machine Learning Applications