Transporting Heavy Payloads with a Humanoid riding a Hoverboard
Simon Armleder, Yupeng Zhang, J. Rogelio Guadarrama-Olvera, Gordon Cheng
Abstract
Driven by the need for rapid and reliable heavy payload transport in logistics and manufacturing, researchers are increasingly exploring early applications of humanoid robotics in these domains. Although bipedal locomotion excels on challenging terrain, wheeled modes of transportation remain significantly more energy-efficient on flat surfaces. In this work, we develop a control system that enables a humanoid robot to achieve fast transportation - by riding a two-wheeled hoverboard - and robust heavy payload handling through whole-body grasping, where the robot uses its chest and arms to stabilize bulky objects. Our approach models payload-induced disturbances using a Linear Inverted Pendulum Mode extended with external forces and leverages tactile feedback from an integrated robotic skin to estimate the payload’s weight and center of mass. Feeding these estimates into the hoverboard controller reduces drift and enhances stability. Experimental evaluations on a full-sized real humanoid robot show that our system can withstand strong disturbances and autonomously navigate to deliver payloads of up to 20 kg.
BibTeX
@inproceedings{iros2025_transportingheav,
title = {Transporting Heavy Payloads with a Humanoid riding a Hoverboard},
author = {Simon Armleder and Yupeng Zhang and J. Rogelio Guadarrama-Olvera and Gordon Cheng},
booktitle = {IROS 2025},
year = {2025}
}