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Journal of Shanghai Jiaotong University(Science) >

2026 , Vol. 31 >Issue 1: 167 - 175

DOI: https://doi.org/10.1007/s12204-025-2807-7

Intelligent Robots

Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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  • 1. School of Software, Southeast University, Suzhou 215000, Jiangsu, China; 2. School of Automation, Southeast University, Nanjing 210018, China; 3. School of Cyber Science and Engineering, Southeast University, Nanjing 211102, China; 4. Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education, Nanjing 214135, China; 5. Nanjing Center for Applied Mathematics, Nanjing 211135, China; 6. Southeast University Shenzhen Research Institute, Shenzhen 518063, Guangdong, China

Received date: 2024-11-13

  Accepted date: 2024-12-02

  Online published: 2026-02-12

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Abstract

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments.

Cite this article

Li Mingwang, Li Xinde, Zhang Zhentong, Wang Zeyu, Zhao Haoming . Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios[J]. Journal of Shanghai Jiaotong University(Science), 2026 , 31(1) : 167 -175 . DOI: 10.1007/s12204-025-2807-7

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