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A High-Payload Robotic Hopper Powered by Bidirectional Thrusters

Song Li (Co-first Author), Songnan Bai (Co-first Author), Ruihan Jia, Yixi Cai, Runze Ding, Yu Shi, Fu Zhang, Pakpong Chirarattananon*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Mobile robots have revolutionized various fields, offering solutions for manipulation, environmental monitoring, and exploration. However, payload capacity remains a limitation. This article presents a novel thrust-based robotic hopper capable of carrying payloads up to nine times its own weight while maintaining agile mobility over less structured terrain. The 220 g robot carries upto 2 kg while hopping--a capability that bridges the gap between high-payload ground robots and agile aerial platforms. Key advancements that enable this high-payload capacity include the integration of bidirectional thrusters, allowing for both upward and downward thrust generation to enhance energy management while hopping. In addition, we present a refined model of dynamics that accounts for heavy payload conditions, particularly for large jumps. To address the increased computational demands, we employ a neural network compression technique, ensuring real-time onboard control. The robot's capabilities are demonstrated through a series of experiments, including leaping over a high obstacle, executing sharp turns with large steps, as well as performing simple autonomous navigation while carrying a 730 g LiDAR payload. This showcases the robot's potential for applications, such as mobile sensing and mapping, in challenging environments.

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Original languageEnglish
Pages (from-to)5307-5326
Number of pages20
JournalIEEE Transactions on Robotics
Volume41
Online published19 Aug 2025
DOIs
Publication statusPublished - 2025

Funding

This work was supportedby the Research Grants Council of the Hong Kong Special Administrative Region of China under Grant CityU 11209024 and Grant PolyU R5006-23.

Research Keywords

  • Robots
  • Legged locomotion
  • Payloads
  • Attitude control
  • Quadrotors
  • Propulsion
  • Propellers
  • Elastomers
  • Computational modeling
  • Trajectory
  • Autonomous navigation
  • high payload
  • hopping
  • legged robots
  • neural network (NN)
  • spring-loaded inverted pendulum (SLIP)

RGC Funding Information

  • RGC-funded

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