HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers
This provides a standardized tool for researchers in robotics to benchmark handover algorithms, though it is incremental as it builds on existing motion capture data.
The paper tackles the problem of simulating human-to-robot object handovers by introducing HandoverSim, a new simulation benchmark, and shows that baseline performance correlates with real-world evaluation.
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. Code is open sourced at https://handover-sim.github.io.