A Novel Telerobotic Search System using an Unmanned Aerial Vehicle

Lu, Bingxian; Wu, Jijie; Tsai, Yu-Chung; Jiang, Wanting; Tseng, Kuo-Shih

doi:10.1109/irc.2020.00030

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…The coordination patterns between gaze and control in human spatial search can be further analyzed [47]. To analyze 3D search behavior, a UAV is remotely controlled by the human subject for collecting data [48]. The collected human data can be also adopted for deep inverse reinforcement learning [49].…”

Section: Discussionmentioning

confidence: 99%

People search via deep compressed sensing techniques

Tsai

Tseng

2022

Robotica

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People search can be reformulated as submodular maximization problems to achieve solutions with theoretical guarantees. However, the number of submodular function outcome is $2^N$ from N sets. Compressing functions via nonlinear Fourier transform and spraying out sets are two ways to overcome this issue. This research proposed the submodular deep compressed sensing of convolutional sparse coding (SDCS-CSC) and applied the Topological Fourier Sparse Set (TFSS) algorithms to solve people search problems. The TFSS is based on topological and compressed sensing techniques, while the CSC is based on DCS techniques. Both algorithms enable an unmanned aerial vehicle to search for the people in environments. Experiments demonstrate that the algorithms can search for the people more efficiently than the benchmark approaches. This research also suggests how to select CSC or TFSS algorithms for different search problems.

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Section: Discussionmentioning

confidence: 99%

People search via deep compressed sensing techniques

Tsai

Tseng

2022

Robotica

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“…Furthermore, a technique that supplements the performance of human operators will also contribute to the SAR performance. The examples are presented in the paper [89], where the gaze data are input DIRL for improving the searching performance of the operator, and the paper [82], where the best video processing technique is chosen to maximize the SAR efficiency of human operators. These techniques may avoid the majority of human factors during the rescue mission, effectively making progress in the operation.…”

Section: Literaturementioning

confidence: 99%

Unmanned Aerial Vehicles for Search and Rescue: A Survey

et al. 2023

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In recent years, unmanned aerial vehicles (UAVs) have gained popularity due to their flexibility, mobility, and accessibility in various fields, including search and rescue (SAR) operations. The use of UAVs in SAR can greatly enhance the task success rates in reaching inaccessible or dangerous areas, performing challenging operations, and providing real-time monitoring and modeling of the situation. This article aims to help readers understand the latest progress and trends in this field by synthesizing and organizing papers related to UAV search and rescue. An introduction to the various types and components of UAVs and their importance in SAR operations is settled first. Additionally, we present a comprehensive review of sensor integrations in UAVs for SAR operations, highlighting their roles in target perception, localization, and identification. Furthermore, we elaborate on the various applications of UAVs in SAR, including on-site monitoring and modeling, perception and localization of targets, and SAR operations such as task assignment, path planning, and collision avoidance. We compare different approaches and methodologies used in different studies, assess the strengths and weaknesses of various approaches, and provide insights on addressing the research questions relating to specific UAV operations in SAR. Overall, this article presents a comprehensive overview of the significant role of UAVs in SAR operations. It emphasizes the vital contributions of drones in enhancing mission success rates, augmenting situational awareness, and facilitating efficient and effective SAR activities. Additionally, the article discusses potential avenues for enhancing the performance of UAVs in SAR.

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Adaptive submodular inverse reinforcement learning for spatial search and map exploration

Tseng

2022

Auton Robot

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A Novel Telerobotic Search System using an Unmanned Aerial Vehicle

Cited by 5 publications

References 9 publications

People search via deep compressed sensing techniques

People search via deep compressed sensing techniques

Unmanned Aerial Vehicles for Search and Rescue: A Survey

Adaptive submodular inverse reinforcement learning for spatial search and map exploration

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