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Design and Integration of Sensors for Control, Planning and Deployment in Robotic Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 424

Special Issue Editors


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Guest Editor
Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart, Germany
Interests: medical robotics; magnetically controlled microrobots; soft robotics; force sensor; force feedback; ultrasound imaging; fetal imaging; force control; robotic system
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190 Beijing, China
Interests: medical robotics; robot-assisted intervention; computer-assisted surgery; sensing and navigation

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Guest Editor
Biomedical Engineering Department, King’s College London, Westminster Bridge Road, SE1 7EH London, UK
Interests: medical robotics, surgical robotics, robotic navigation, ultrasound imaging, fetal imaging, cardiac imaging

Special Issue Information

Dear Colleagues,

In an era where robotics is transcending traditional boundaries, the role of sensors in enhancing robotic capabilities has never been more pivotal. The design and integration of advanced sensors are crucial for enabling robots to navigate complex environments, make autonomous decisions, and interact intelligently with their surroundings. This evolution marks a significant leap towards creating more adaptive, responsive, and functional robotic systems capable of tackling real-world challenges across various domains. The importance of sensing technologies cannot be overstated, as they pave the way for next-generation robotics to perform more complex, adaptive, and collaborative tasks. Despite the remarkable progress, the field still faces significant challenges that hinder the full realization of sensor-enabled robotics' potential. 

This Special Issue of Sensors (MDPI), entitled "Design and Integration of Sensors for Control, Planning and Deployment in Robotic Systems", focuses on the critical aspects of sensor design, manufacturing, and their integration into robotic systems for enhanced control, planning, and deployment. We invite research and review papers that introduce novel developments in sensing technologies, fabrication processes, and their application in robotics.

Dr. Xianqiang Bao
Prof. Dr. Shuangyi Wang
Dr. James Housden
Guest Editors

Manuscript Submission Information

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Keywords

  • sensor design
  • advanced sensor technologies
  • sensor fabrication methods
  • robotic control systems
  • autonomous decision-making
  • sensor fusion technologies
  • flexible sensors
  • smart sensing materials
  • multimodal sensor integration
  • environmental sensing

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Published Papers (1 paper)

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Research

14 pages, 12144 KiB  
Article
NMC3D: Non-Overlapping Multi-Camera Calibration Based on Sparse 3D Map
by Changshuai Dai, Ting Han, Yang Luo, Mengyi Wang, Guorong Cai, Jinhe Su, Zheng Gong and Niansheng Liu
Sensors 2024, 24(16), 5228; https://doi.org/10.3390/s24165228 (registering DOI) - 13 Aug 2024
Viewed by 186
Abstract
With the advancement of computer vision and sensor technologies, many multi-camera systems are being developed for the control, planning, and other functionalities of unmanned systems or robots. The calibration of multi-camera systems determines the accuracy of their operation. However, calibration of multi-camera systems [...] Read more.
With the advancement of computer vision and sensor technologies, many multi-camera systems are being developed for the control, planning, and other functionalities of unmanned systems or robots. The calibration of multi-camera systems determines the accuracy of their operation. However, calibration of multi-camera systems without overlapping parts is inaccurate. Furthermore, the potential of feature matching points and their spatial extent in calculating the extrinsic parameters of multi-camera systems has not yet been fully realized. To this end, we propose a multi-camera calibration algorithm to solve the problem of the high-precision calibration of multi-camera systems without overlapping parts. The calibration of multi-camera systems is simplified to the problem of solving the transformation relationship of extrinsic parameters using a map constructed by multiple cameras. Firstly, the calibration environment map is constructed by running the SLAM algorithm separately for each camera in the multi-camera system in closed-loop motion. Secondly, uniformly distributed matching points are selected among the similar feature points between the maps. Then, these matching points are used to solve the transformation relationship between the multi-camera external parameters. Finally, the reprojection error is minimized to optimize the extrinsic parameter transformation relationship. We conduct comprehensive experiments in multiple scenarios and provide results of the extrinsic parameters for multiple cameras. The results demonstrate that the proposed method accurately calibrates the extrinsic parameters for multiple cameras, even under conditions where the main camera and auxiliary cameras rotate 180°. Full article
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