Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation

Zhiheng Liang; Yewei Lu; Zhenhua Wang

doi:10.1109/CCDC69976.2026.11560667

Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation

Zhiheng Liang
, Yewei Lu
, Zhenhua Wang

School of Astronautics, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Reliable collision detection is critical for high-speed operation of dual-arm Selective Compliance Assembly Robot Arm (SCARA) robots. This paper presents a collision detection framework based on a generalized-momentum extended state observer (ESO) with parameter uncertainty compensation. First, a dynamic model of a dual-arm SCARA robot is established under belt-driven geometric constraints. Then, considering inertial parameter uncertainty, a momentum-based ESO with parameter uncertainty compensation is developed to estimate external joint torques without inertia matrix inversion or jointacceleration measurements. Simulation studies involving rigid and compliant contact scenarios demonstrate that the proposed method achieves reliable and timely collision detection with lower usable thresholds in the presence of parameter uncertainty.

Original language	English
Title of host publication	38th Chinese Control and Decision Conference, CCDC 2026
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6561-6566
Number of pages	6
ISBN (Electronic)	9798331550707
DOIs	https://doi.org/10.1109/CCDC69976.2026.11560667
State	Published - 2026
Externally published	Yes
Event	38th Chinese Control and Decision Conference, CCDC 2026 - Nanjing, China Duration: 15 May 2026 → 18 May 2026

Publication series

Name	38th Chinese Control and Decision Conference, CCDC 2026

Conference

Conference	38th Chinese Control and Decision Conference, CCDC 2026
Country/Territory	China
City	Nanjing
Period	15/05/26 → 18/05/26

Keywords

collision detection
dual-arm SCARA robot
extended state observer
parameter uncertainty compensation

Access to Document

10.1109/CCDC69976.2026.11560667

Cite this

Liang, Z., Lu, Y., & Wang, Z. (2026). Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation. In 38th Chinese Control and Decision Conference, CCDC 2026 (pp. 6561-6566). (38th Chinese Control and Decision Conference, CCDC 2026). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC69976.2026.11560667

@inproceedings{fe925d5493d048ecb6c96067fb787b15,

title = "Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation",

abstract = "Reliable collision detection is critical for high-speed operation of dual-arm Selective Compliance Assembly Robot Arm (SCARA) robots. This paper presents a collision detection framework based on a generalized-momentum extended state observer (ESO) with parameter uncertainty compensation. First, a dynamic model of a dual-arm SCARA robot is established under belt-driven geometric constraints. Then, considering inertial parameter uncertainty, a momentum-based ESO with parameter uncertainty compensation is developed to estimate external joint torques without inertia matrix inversion or jointacceleration measurements. Simulation studies involving rigid and compliant contact scenarios demonstrate that the proposed method achieves reliable and timely collision detection with lower usable thresholds in the presence of parameter uncertainty.",

keywords = "collision detection, dual-arm SCARA robot, extended state observer, parameter uncertainty compensation",

author = "Zhiheng Liang and Yewei Lu and Zhenhua Wang",

note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 38th Chinese Control and Decision Conference, CCDC 2026 ; Conference date: 15-05-2026 Through 18-05-2026",

year = "2026",

doi = "10.1109/CCDC69976.2026.11560667",

language = "英语",

series = "38th Chinese Control and Decision Conference, CCDC 2026",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "6561--6566",

booktitle = "38th Chinese Control and Decision Conference, CCDC 2026",

address = "美国",

}

Liang, Z, Lu, Y & Wang, Z 2026, Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation. in 38th Chinese Control and Decision Conference, CCDC 2026. 38th Chinese Control and Decision Conference, CCDC 2026, Institute of Electrical and Electronics Engineers Inc., pp. 6561-6566, 38th Chinese Control and Decision Conference, CCDC 2026, Nanjing, China, 15/05/26. https://doi.org/10.1109/CCDC69976.2026.11560667

Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation. / Liang, Zhiheng; Lu, Yewei; Wang, Zhenhua.
38th Chinese Control and Decision Conference, CCDC 2026. Institute of Electrical and Electronics Engineers Inc., 2026. p. 6561-6566 (38th Chinese Control and Decision Conference, CCDC 2026).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation

AU - Liang, Zhiheng

AU - Lu, Yewei

AU - Wang, Zhenhua

PY - 2026

Y1 - 2026

N2 - Reliable collision detection is critical for high-speed operation of dual-arm Selective Compliance Assembly Robot Arm (SCARA) robots. This paper presents a collision detection framework based on a generalized-momentum extended state observer (ESO) with parameter uncertainty compensation. First, a dynamic model of a dual-arm SCARA robot is established under belt-driven geometric constraints. Then, considering inertial parameter uncertainty, a momentum-based ESO with parameter uncertainty compensation is developed to estimate external joint torques without inertia matrix inversion or jointacceleration measurements. Simulation studies involving rigid and compliant contact scenarios demonstrate that the proposed method achieves reliable and timely collision detection with lower usable thresholds in the presence of parameter uncertainty.

AB - Reliable collision detection is critical for high-speed operation of dual-arm Selective Compliance Assembly Robot Arm (SCARA) robots. This paper presents a collision detection framework based on a generalized-momentum extended state observer (ESO) with parameter uncertainty compensation. First, a dynamic model of a dual-arm SCARA robot is established under belt-driven geometric constraints. Then, considering inertial parameter uncertainty, a momentum-based ESO with parameter uncertainty compensation is developed to estimate external joint torques without inertia matrix inversion or jointacceleration measurements. Simulation studies involving rigid and compliant contact scenarios demonstrate that the proposed method achieves reliable and timely collision detection with lower usable thresholds in the presence of parameter uncertainty.

KW - collision detection

KW - dual-arm SCARA robot

KW - extended state observer

KW - parameter uncertainty compensation

UR - https://www.scopus.com/pages/publications/105043920226

U2 - 10.1109/CCDC69976.2026.11560667

DO - 10.1109/CCDC69976.2026.11560667

M3 - 会议稿件

AN - SCOPUS:105043920226

T3 - 38th Chinese Control and Decision Conference, CCDC 2026

SP - 6561

EP - 6566

BT - 38th Chinese Control and Decision Conference, CCDC 2026

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 38th Chinese Control and Decision Conference, CCDC 2026

Y2 - 15 May 2026 through 18 May 2026

ER -

Collision Detection for Dual-Arm SCARA Robots Using Momentum-Based ESO with Parameter Uncertainty Compensation

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this