Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing

Shang Liu; Xiaobao Wei; Lulu Wang; Jing Zhang; Boyu Li; Haosong Yue

doi:10.1007/978-981-19-6613-2_263

Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing

Shang Liu
, Xiaobao Wei
, Lulu Wang
, Jing Zhang
, Boyu Li^*
, Haosong Yue

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Beihang University
Northwest Agriculture and Forestry University
Beijing Institute of Aeronautical Materials

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

2 Scopus citations

Abstract

Gravity-induced extra moments may cause the robotic arm to drop things with an unequal mass distribution. In order to address this issue, we provide a unique technique, which extra wrists and touch sensors or a huge number of tests are not needed. As a first step, we measure the rod object’s center of mass using the robot arm’s commonly fixed joint torque sensors and RGBD cameras. The approach for improving the stability of grasping is also provided. In “Mujoco,” simulation experiments are undertaken. Results indicate that our efforts to improve gripping robustness have been successful.

Original language	English
Title of host publication	Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control
Editors	Liang Yan, Haibin Duan, Yimin Deng, Liang Yan
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	2699-2708
Number of pages	10
ISBN (Print)	9789811966125
DOIs	https://doi.org/10.1007/978-981-19-6613-2_263
State	Published - 2023
Event	International Conference on Guidance, Navigation and Control, ICGNC 2022 - Harbin, China Duration: 5 Aug 2022 → 7 Aug 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	845 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Guidance, Navigation and Control, ICGNC 2022
Country/Territory	China
City	Harbin
Period	5/08/22 → 7/08/22

Keywords

Center of mass estimation
Force sensor
Grasp pose adaptation

Access to Document

10.1007/978-981-19-6613-2_263

Cite this

Liu, S., Wei, X., Wang, L., Zhang, J., Li, B., & Yue, H. (2023). Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing. In L. Yan, H. Duan, Y. Deng, & L. Yan (Eds.), Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control (pp. 2699-2708). (Lecture Notes in Electrical Engineering; Vol. 845 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-6613-2_263

Liu, Shang ; Wei, Xiaobao ; Wang, Lulu et al. / Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing. Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. editor / Liang Yan ; Haibin Duan ; Yimin Deng ; Liang Yan. Springer Science and Business Media Deutschland GmbH, 2023. pp. 2699-2708 (Lecture Notes in Electrical Engineering).

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title = "Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing",

abstract = "Gravity-induced extra moments may cause the robotic arm to drop things with an unequal mass distribution. In order to address this issue, we provide a unique technique, which extra wrists and touch sensors or a huge number of tests are not needed. As a first step, we measure the rod object{\textquoteright}s center of mass using the robot arm{\textquoteright}s commonly fixed joint torque sensors and RGBD cameras. The approach for improving the stability of grasping is also provided. In “Mujoco,” simulation experiments are undertaken. Results indicate that our efforts to improve gripping robustness have been successful.",

keywords = "Center of mass estimation, Force sensor, Grasp pose adaptation",

author = "Shang Liu and Xiaobao Wei and Lulu Wang and Jing Zhang and Boyu Li and Haosong Yue",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2022 ; Conference date: 05-08-2022 Through 07-08-2022",

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Liu, S, Wei, X, Wang, L, Zhang, J, Li, B & Yue, H 2023, Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing. in L Yan, H Duan, Y Deng & L Yan (eds), Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. Lecture Notes in Electrical Engineering, vol. 845 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 2699-2708, International Conference on Guidance, Navigation and Control, ICGNC 2022, Harbin, China, 5/08/22. https://doi.org/10.1007/978-981-19-6613-2_263

Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing. / Liu, Shang; Wei, Xiaobao; Wang, Lulu et al.
Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. ed. / Liang Yan; Haibin Duan; Yimin Deng; Liang Yan. Springer Science and Business Media Deutschland GmbH, 2023. p. 2699-2708 (Lecture Notes in Electrical Engineering; Vol. 845 LNEE).

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

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AU - Li, Boyu

AU - Yue, Haosong

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AB - Gravity-induced extra moments may cause the robotic arm to drop things with an unequal mass distribution. In order to address this issue, we provide a unique technique, which extra wrists and touch sensors or a huge number of tests are not needed. As a first step, we measure the rod object’s center of mass using the robot arm’s commonly fixed joint torque sensors and RGBD cameras. The approach for improving the stability of grasping is also provided. In “Mujoco,” simulation experiments are undertaken. Results indicate that our efforts to improve gripping robustness have been successful.

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Liu S, Wei X, Wang L, Zhang J, Li B, Yue H. Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing. In Yan L, Duan H, Deng Y, Yan L, editors, Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. Springer Science and Business Media Deutschland GmbH. 2023. p. 2699-2708. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-19-6613-2_263