AeroHaptix: A Wearable Vibrotactile Feedback System for Enhancing Collision Avoidance in UAV Teleoperation

被引:0
|
作者
Huang, Bingjian [1 ]
Wang, Zhecheng [1 ]
Cheng, Qilong [1 ]
Ren, Siyi [1 ]
Cai, Hanfeng [1 ]
Valdivia, Antonio Alvarez [2 ]
Mahadevan, Karthik [1 ]
Wigdor, Daniel [1 ]
机构
[1] Univ Toronto, Dynam Graph Project Lab, Toronto, ON M5S 2E4, Canada
[2] Purdue Univ, Mech Engn, W Lafayette, IN 47901 USA
来源
IEEE ROBOTICS AND AUTOMATION LETTERS | 2025年 / 10卷 / 05期
关键词
Telerobotics and teleoperation; haptics and haptic interfaces; collision avoidance;
D O I
10.1109/LRA.2025.3548866
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Haptic feedback enhances collision avoidance by providing directional obstacle information to operators during unmanned aerial vehicle (UAV) teleoperation. However, such feedback is often rendered via haptic joysticks, which are unfamiliar to UAV operators and limited to single-direction force feedback. Additionally, the direct coupling between the input device and the feedback method diminishes operators' sense of control and induces oscillatory movements. To overcome these limitations, we propose AeroHaptix, a wearable haptic feedback system that uses spatial vibrations to simultaneously communicate multiple obstacle directions to operators, without interfering with their input control. The layout of vibrotactile actuators was optimized via a perceptual study to eliminate perceptual biases and achieve uniform spatial coverage. A novel rendering algorithm, MultiCBF, extended control barrier functions to support multi-directional feedback. Our system evaluation showed that compared to a no-feedback condition, AeroHaptix effectively reduced the number of collisions and input disagreement. Furthermore, operators reported that AeroHaptix was more helpful than force feedback, with improved situational awareness and comparable workload.
引用
收藏
页码:4260 / 4267
页数:8
相关论文
共 47 条
  • [31] Development of collision avoidance system for useful UAV applications using image sensors with laser transmitter
    Cheong, M. K.
    Bahiki, M. R.
    Azrad, S.
    AEROTECH VI - INNOVATION IN AEROSPACE ENGINEERING AND TECHNOLOGY, 2016, 152
  • [32] Deep Learning-Driven Resource Allocation for MEC-Enabled UAV Collision Avoidance System
    Zairi, Khadidja
    Brik, Bouziane
    Guellouma, Younes
    Cherroun, Hadda
    20TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE, IWCMC 2024, 2024, : 1412 - 1417
  • [33] The applicability of on-line contextual calibration to a neural network based monocular collision avoidance system on a UAV
    Hiba, Antal
    Aleksziev, Rita
    Pazman, Koppany
    Bauer, Peter
    Benczur, Andras
    Zarandy, Akos
    Daroczy, Balint
    IFAC PAPERSONLINE, 2019, 52 (11): : 7 - 12
  • [34] Path Planning and Collision Avoidance of Multiple UAV System Based on Particle Swarm Optimization with Kinematic Consideration
    Cheng, Yu-Ju
    Shui, Hsiu-Tsu
    Chen, Chih-Chun
    Lai, Ying-Chih
    JOURNAL OF AERONAUTICS ASTRONAUTICS AND AVIATION, 2024, 56 (01): : 65 - 75
  • [35] Complexed MR laser detector and LWIR camera optical system with neural network management for UAV collision avoidance system
    Polyakov, V. M.
    Kaliteevsky, I. N.
    Amelin, K. S.
    Smyslov, V. A.
    Permyakov, M. A.
    2018 INTERNATIONAL CONFERENCE LASER OPTICS (ICLO 2018), 2018, : 280 - 280
  • [36] UAV Autonomous Collision Avoidance Method Based on Three-dimensional Dynamic Collision Region Model and Interfered Fluid Dynamical System
    Liu, Chang
    Wang, Hong-lun
    Yao, Peng
    INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA 2016), 2016, : 263 - 269
  • [37] Large-Scale Fixed-Wing UAV Swarm System Control With Collision Avoidance and Formation Maneuver
    Li, Jiacheng
    Fang, Yangwang
    Cheng, Haoyun
    Wang, Zhikai
    Wu, Zihao
    Zeng, Mengjie
    IEEE SYSTEMS JOURNAL, 2023, 17 (01): : 744 - 755
  • [38] On the Validation of a UAV Collision Avoidance System Developed by Model-Based Optimization: Challenges and a Tentative Partial Solution
    Zou, Xueyi
    Alexander, Rob
    McDermid, John
    2016 46TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS WORKSHOPS (DSN-W), 2016, : 192 - 199
  • [39] Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept
    Xu, Junkai
    Bao, Tian
    Lee, Ung Hee
    Kinnaird, Catherine
    Carender, Wendy
    Huang, Yangjian
    Sienko, Kathleen H.
    Shull, Peter B.
    JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2017, 14
  • [40] Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept
    Junkai Xu
    Tian Bao
    Ung Hee Lee
    Catherine Kinnaird
    Wendy Carender
    Yangjian Huang
    Kathleen H. Sienko
    Peter B. Shull
    Journal of NeuroEngineering and Rehabilitation, 14