Anzheng Zhang

dblp:358/1276 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Legged, aerial and field robots · 91% Motion planning and robot control · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
legged robots
0.812024
Pegasus: a Novel Bio-inspired Quadruped Robot with Underactuated Wheeled-Legged Mechanism · ICRA 2024
Robotics › Legged, aerial and field robots › legged robots
quadruped robot
0.812024
Pegasus: a Novel Bio-inspired Quadruped Robot with Underactuated Wheeled-Legged Mechanism · ICRA 2024
Robotics › Legged, aerial and field robots
wheel-legged robot
0.812024
Pegasus: a Novel Bio-inspired Quadruped Robot with Underactuated Wheeled-Legged Mechanism · ICRA 2024
Robotics › Motion planning and robot control › robot control
model predictive control
0.212024
Pegasus: a Novel Bio-inspired Quadruped Robot with Underactuated Wheeled-Legged Mechanism · ICRA 2024

Methods — techniques the papers use, named apart from their topics

model predictive control · 0.8adaptive dynamics · 0.8
YearPublicationVenuePosition
2024 Pegasus: a Novel Bio-inspired Quadruped Robot with Underactuated Wheeled-Legged Mechanism
abstract
This paper presents the design and analysis of Pegasus, a quadrupedal wheeled robot grounded in biomimicry principles. Pegasus offers two distinct motion modes, including a wheeled motion and a hybrid wheeled-legged motion, enabling adaptability across various tasks and environmental conditions. The robot draws inspiration from the joint structures of quadruped animals and incorporates biomimetic features. At the robot’s ankle joint, we imitate the articulation of a radiusulna joint to enhance the wheeled motion’s agility. Additionally, we establish comprehensive mathematical models for adaptive dynamics model, providing a robust theoretical foundation for subsequent motion planning and high-precision control. A novel telescopic vehicle mode is also proposed for complex wheel-leg hybrid motion, offering optimized solutions for intricate robot locomotion. Furthermore, we employ parallel underactuated MPC controllers for each leg at the control level, contributing to heightened motion precision and stability. Extensive validation through physical platform experiments highlights the effectiveness and feasibility of the proposed controllers, offering substantial support for real-world applications in robotics.
Yuzhen Pan, Rezwan Al Islam Khan, Chenyun Zhang, Anzheng Zhang
ICRA4