Real-time collision avoidance in a dynamic environment for an industrial robotic arm

Uchenna Emeoha Ogenyi; Qing Gao; Dalin Zhou; Charles Chimwemwe Phiri; Zhaojie Ju; Honghai Liu

doi:10.1007/978-3-030-89098-8_11

Real-time collision avoidance in a dynamic environment for an industrial robotic arm

Uchenna Emeoha Ogenyi^*, Qing Gao, Dalin Zhou, Charles Chimwemwe Phiri, Zhaojie Ju, Honghai Liu

^*Corresponding author for this work

School of Computing

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

88 Downloads (Pure)

Abstract

This paper proposed learning from demonstration control policy that permits generalisation in an unstructured and dynamic environment. The approach combines a probabilistic model with a reactive approach that learns the cost function of an unknown state of the environmental constraints. The approach redefines the robot’s behaviour towards a trajectory that satisfies both the task and scene constraints, facilitating enhanced human-robot coexistence.

Original language	English
Title of host publication	ICIRA 2021: International Conference on Intelligent Robotics and Applications
Subtitle of host publication	14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part II
Editors	Xin-Jun Liu, Zhenguo Nie, Jingjun Yu, Fugui Xie, Rui Song
Publisher	Springer
Pages	111-121
Number of pages	11
ISBN (Electronic)	9783030890988
ISBN (Print)	9783030890971
DOIs	https://doi.org/10.1007/978-3-030-89098-8_11
Publication status	Published - 18 Oct 2021
Event	ICIRA 2021: 14th International Conference on Intelligent Robotics and Applications - Yantai, China Duration: 22 Oct 2021 → 25 Oct 2021

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	13014
ISSN (Print)	0302-9743

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
Volume	13014
ISSN (Electronic)	1611-3349

Conference

Conference	ICIRA 2021: 14th International Conference on Intelligent Robotics and Applications
Country/Territory	China
City	Yantai
Period	22/10/21 → 25/10/21

Keywords

robot learning from demonstration
dynamic obstacle
probabilistic modelling

Access to Document

10.1007/978-3-030-89098-8_11

Real-time Collision Avoidance in a Dynamic Environment
This is a post-peer-review, pre-copyedit version of an article published in Ogenyi U.E., Gao Q., Zhou D., Phiri C., Ju Z., Liu H. (2021) Real-Time Collision Avoidance in a Dynamic Environment for an Industrial Robotic Arm. In: Liu XJ., Nie Z., Yu J., Xie F., Song R. (eds) Intelligent Robotics and Applications. ICIRA 2021. Lecture Notes in Computer Science, vol 13014. Springer, Cham. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-89098-8_11.
Accepted author manuscript (Post-print), 1.54 MB

Cite this

Ogenyi, U. E., Gao, Q., Zhou, D., Phiri, C. C., Ju, Z., & Liu, H. (2021). Real-time collision avoidance in a dynamic environment for an industrial robotic arm. In X.-J. Liu, Z. Nie, J. Yu, F. Xie, & R. Song (Eds.), ICIRA 2021: International Conference on Intelligent Robotics and Applications: 14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part II (pp. 111-121). (Lecture Notes in Computer Science; Vol. 13014), (Lecture Notes in Artificial Intelligence; Vol. 13014). Springer. https://doi.org/10.1007/978-3-030-89098-8_11

Ogenyi, Uchenna Emeoha ; Gao, Qing ; Zhou, Dalin et al. / Real-time collision avoidance in a dynamic environment for an industrial robotic arm. ICIRA 2021: International Conference on Intelligent Robotics and Applications: 14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part II. editor / Xin-Jun Liu ; Zhenguo Nie ; Jingjun Yu ; Fugui Xie ; Rui Song. Springer, 2021. pp. 111-121 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence).

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title = "Real-time collision avoidance in a dynamic environment for an industrial robotic arm",

abstract = "This paper proposed learning from demonstration control policy that permits generalisation in an unstructured and dynamic environment. The approach combines a probabilistic model with a reactive approach that learns the cost function of an unknown state of the environmental constraints. The approach redefines the robot{\textquoteright}s behaviour towards a trajectory that satisfies both the task and scene constraints, facilitating enhanced human-robot coexistence.",

keywords = "robot learning from demonstration, dynamic obstacle, probabilistic modelling",

author = "Ogenyi, {Uchenna Emeoha} and Qing Gao and Dalin Zhou and Phiri, {Charles Chimwemwe} and Zhaojie Ju and Honghai Liu",

year = "2021",

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language = "English",

isbn = "9783030890971",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

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editor = "Xin-Jun Liu and Zhenguo Nie and Jingjun Yu and Fugui Xie and Rui Song",

booktitle = "ICIRA 2021: International Conference on Intelligent Robotics and Applications",

note = "ICIRA 2021: 14th International Conference on Intelligent Robotics and Applications ; Conference date: 22-10-2021 Through 25-10-2021",

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Ogenyi, UE, Gao, Q, Zhou, D, Phiri, CC, Ju, Z & Liu, H 2021, Real-time collision avoidance in a dynamic environment for an industrial robotic arm. in X-J Liu, Z Nie, J Yu, F Xie & R Song (eds), ICIRA 2021: International Conference on Intelligent Robotics and Applications: 14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part II. Lecture Notes in Computer Science, vol. 13014, Lecture Notes in Artificial Intelligence, vol. 13014, Springer, pp. 111-121, ICIRA 2021: 14th International Conference on Intelligent Robotics and Applications, Yantai, China, 22/10/21. https://doi.org/10.1007/978-3-030-89098-8_11

Real-time collision avoidance in a dynamic environment for an industrial robotic arm. / Ogenyi, Uchenna Emeoha; Gao, Qing; Zhou, Dalin et al.
ICIRA 2021: International Conference on Intelligent Robotics and Applications: 14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part II. ed. / Xin-Jun Liu; Zhenguo Nie; Jingjun Yu; Fugui Xie; Rui Song. Springer, 2021. p. 111-121 (Lecture Notes in Computer Science; Vol. 13014), (Lecture Notes in Artificial Intelligence; Vol. 13014).

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

TY - GEN

T1 - Real-time collision avoidance in a dynamic environment for an industrial robotic arm

AU - Ogenyi, Uchenna Emeoha

AU - Gao, Qing

AU - Zhou, Dalin

AU - Phiri, Charles Chimwemwe

AU - Ju, Zhaojie

AU - Liu, Honghai

PY - 2021/10/18

Y1 - 2021/10/18

N2 - This paper proposed learning from demonstration control policy that permits generalisation in an unstructured and dynamic environment. The approach combines a probabilistic model with a reactive approach that learns the cost function of an unknown state of the environmental constraints. The approach redefines the robot’s behaviour towards a trajectory that satisfies both the task and scene constraints, facilitating enhanced human-robot coexistence.

AB - This paper proposed learning from demonstration control policy that permits generalisation in an unstructured and dynamic environment. The approach combines a probabilistic model with a reactive approach that learns the cost function of an unknown state of the environmental constraints. The approach redefines the robot’s behaviour towards a trajectory that satisfies both the task and scene constraints, facilitating enhanced human-robot coexistence.

KW - robot learning from demonstration

KW - dynamic obstacle

KW - probabilistic modelling

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DO - 10.1007/978-3-030-89098-8_11

M3 - Conference contribution

SN - 9783030890971

T3 - Lecture Notes in Computer Science

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BT - ICIRA 2021: International Conference on Intelligent Robotics and Applications

A2 - Liu, Xin-Jun

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A2 - Xie, Fugui

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PB - Springer

T2 - ICIRA 2021: 14th International Conference on Intelligent Robotics and Applications

Y2 - 22 October 2021 through 25 October 2021

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Ogenyi UE, Gao Q, Zhou D, Phiri CC, Ju Z , Liu H. Real-time collision avoidance in a dynamic environment for an industrial robotic arm. In Liu XJ, Nie Z, Yu J, Xie F, Song R, editors, ICIRA 2021: International Conference on Intelligent Robotics and Applications: 14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part II. Springer. 2021. p. 111-121. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). doi: 10.1007/978-3-030-89098-8_11

Real-time collision avoidance in a dynamic environment for an industrial robotic arm

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