A Practical Trajectory Planning Method for Smooth and Fast Xylophone Playing with a Six-Axis Robotic Arm

One major challenge in enabling a six-axis robotic arm to play the xylophone is generating smooth trajectories that prevent motor overload during high-speed performance. This paper proposes two practical trajectory planning strategies-fluid trajectory and low-variation trajectory-based on a hybrid use of bang-bang trajectories and cubic polynomial trajectories. It also presents a complete solution addressing key implementation details, such as connection point pose optimization and IK branch selection. Experiments demonstrate that the fluid trajectory offers more graceful motion, adapting visually to rhythmic changes in music, while the low-variation trajectory reduces joint movement near the base, thereby suppressing vibration-induced noise during fast motions.

Authors

Institutions

Publication Details

Published
2025-07-11
DOI
https://doi.org/10.1109/ieeeconf65522.2025.11137143
Primary Topic
Control and Dynamics of Mobile Robots
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Practical Trajectory Planning Method for Smooth and Fast Xylophone Playing with a Six-Axis Robotic Arm

Yunjiang Lou, Hui Du, Mingyu Deng
Control and Dynamics of Mobile Robots
article

A Practical Trajectory Planning Method for Smooth and Fast Xylophone Playing with a Six-Axis Robotic Arm

Yunjiang Lou, Hui Du, Mingyu Deng
article en

Abstract

One major challenge in enabling a six-axis robotic arm to play the xylophone is generating smooth trajectories that prevent motor overload during high-speed performance. This paper proposes two practical trajectory planning strategies-fluid trajectory and low-variation trajectory-based on a hybrid use of bang-bang trajectories and cubic polynomial trajectories. It also presents a complete solution addressing key implementation details, such as connection point pose optimization and IK branch selection. Experiments demonstrate that the fluid trajectory offers more graceful motion, adapting visually to rhythmic changes in music, while the low-variation trajectory reduces joint movement near the base, thereby suppressing vibration-induced noise during fast motions.

Shenzhen Institute of Information Technology (CN), Harbin Institute of Technology (CN), Shenzhen Academy of Robotics (CN)
Openalex Percentile: Top 71%
Control and Dynamics of Mobile Robots
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.