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.
© 2025 IEEE. All rights reserved, including rights for text and data mining, and training of artificial intelligence and similar technologies. Personal use is permitted, but republication/redistribution requires IEEE permission
© 2025 IEEE. All rights reserved, including rights for text and data mining, and training of artificial intelligence and similar technologies. Personal use is permitted, but republication/redistribution requires IEEE permission
| Original language | English |
|---|---|
| Pages (from-to) | 5307-5326 |
| Number of pages | 20 |
| Journal | IEEE Transactions on Robotics |
| Volume | 41 |
| Online published | 19 Aug 2025 |
| DOIs | |
| Publication status | Published - 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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GRF: Hopping Aerial Robots: Reaching New Heights across Size Scales through Thrust-based and Parallel Elastic Actuation
ZHANG, J. (Principal Investigator / Project Coordinator)
1/01/25 → …
Project: Research
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RIF-ExtU-Lead: Digital Twin-enabled Intelligent Assessment and Maintenance of Offshore Wind Turbine Structures in a Life-cycle Context
ZHU, S. (Main Project Coordinator [External]) & CHIRARATTANANON, P. (Principal Investigator / Project Coordinator)
30/06/24 → 21/01/26
Project: Research
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