Shared Control With Obstacle Avoidance for UGVs

Uncrewed ground vehicle (UGV) applications, such as warehouse operations, assembly-line production, infrastructure inspection, surveillance, precision farming, and search & rescue, can benefit from shared control, in which a human can semi-automatically control the UGV when needed and let it operate fully-automatically, when desired. Many algorithms have been developed to permit a UGV to semi-autonomously conduct tasks, either individually, or in a group. However, a complete semi-autonomous system that works wherever, and whenever, needed is far from being implemented. Here, we develop a human-robot shared controller for the supervisory control of one or more UGVs by a single person. The shared controller blends an automatic control input with a human control input. The automatic control input consists of a trajectory tracking controller and a control barrier function based input term for collision avoidance. A joystick is used to provide the human control input. Human intent is measured employing a Lyapunov-like storage function, which is used in a convex function based blending law that continuously varies the magnitude of the control inputs coming from the human and the machine. The approach permits us to theoretically prove the asymptotic stability of the closed-loop system. The shared controller is validated using both a physical robot in a cluttered indoor environment, and a hardware-in-the-loop simulated robot operating in virtual warehouse environment.

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Publication Details

Journal
IEEE Transactions on Automation Science and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tase.2025.3582522
Citations
2
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
1.46
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article

Shared Control With Obstacle Avoidance for UGVs

Karl D. von Ellenrieder, Cheikh Melainine El Bou, Satyandra K. Gupta, Florian Beck
2 citations
IEEE Transactions on Automation Science and Engineering
Advanced Wireless Network Optimization
1.46
article

Shared Control With Obstacle Avoidance for UGVs

Karl D. von Ellenrieder, Cheikh Melainine El Bou, Satyandra K. Gupta, Florian Beck
article en
2 citations

Abstract

Uncrewed ground vehicle (UGV) applications, such as warehouse operations, assembly-line production, infrastructure inspection, surveillance, precision farming, and search & rescue, can benefit from shared control, in which a human can semi-automatically control the UGV when needed and let it operate fully-automatically, when desired. Many algorithms have been developed to permit a UGV to semi-autonomously conduct tasks, either individually, or in a group. However, a complete semi-autonomous system that works wherever, and whenever, needed is far from being implemented. Here, we develop a human-robot shared controller for the supervisory control of one or more UGVs by a single person. The shared controller blends an automatic control input with a human control input. The automatic control input consists of a trajectory tracking controller and a control barrier function based input term for collision avoidance. A joystick is used to provide the human control input. Human intent is measured employing a Lyapunov-like storage function, which is used in a convex function based blending law that continuously varies the magnitude of the control inputs coming from the human and the machine. The approach permits us to theoretically prove the asymptotic stability of the closed-loop system. The shared controller is validated using both a physical robot in a cluttered indoor environment, and a hardware-in-the-loop simulated robot operating in virtual warehouse environment.

IEEE Transactions on Automation Science and EngineeringVol. 22
University of Southern California (US), Free University of Bozen-Bolzano (IT)
Climate action
Openalex Percentile: Top 17%
Advanced Wireless Network Optimization
1.46
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Shared Control With Obstacle Avoidance for UGVs — Karl D. von Ellenrieder, Cheikh Melainine El Bou, et al. · IEEE Transactions on Automation Science and Engineering (2025) | TGRS Research Map | TGRS