Stories with Tag autonomous navigation

• Raspberry Pi Lidar Scanner

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  Posted: 2025-04-19 18:53:32

  Verbose tl;dr

  PiLiDAR is a project demonstrating a low-cost, DIY LiDAR scanner built using a Raspberry Pi. It leverages a readily available RPLiDAR A1M8 sensor, Python code, and a simple mechanical setup involving a servo motor to rotate the LiDAR unit, creating 360-degree scans. The project provides complete instructions and software, allowing users to easily build their own LiDAR system for applications like robotics, mapping, and 3D scanning. The provided Python scripts handle data acquisition, processing, and visualization, outputting point cloud data that can be further analyzed or used with other software.

  This GitHub repository, titled "PiLiDAR," details a project focused on creating a 2D LiDAR scanner using a Raspberry Pi. The project leverages the affordability and versatility of the Raspberry Pi platform to construct a cost-effective LiDAR system suitable for various applications. The core of the system revolves around a RPLIDAR A1M8 360-degree laser scanner, known for its compact size and relatively low cost compared to other LiDAR units. The Raspberry Pi acts as the central processing unit, handling data acquisition from the LiDAR sensor, processing that data, and subsequently visualizing it.

  The provided documentation outlines the necessary hardware components beyond the Raspberry Pi and the RPLIDAR, such as a suitable power supply to drive both devices, and the physical mounting mechanisms required to securely affix the LiDAR unit. The software aspect of the project involves utilizing the RPLIDAR's SDK (Software Development Kit), which provides the necessary libraries and functions for communicating with and controlling the LiDAR sensor. Detailed instructions for installing the SDK on the Raspberry Pi's operating system (Raspbian, specifically) are included, ensuring users can correctly configure their system for data acquisition. Furthermore, the repository likely provides code examples and scripts demonstrating how to capture the raw LiDAR data, which typically consists of distance measurements at various angles.

  This captured data can then be further processed and visualized using various methods, potentially including creating 2D point cloud representations of the scanned environment. The visualization process allows users to interpret the LiDAR data and see a representation of the surrounding objects and their distances from the scanner. While the primary focus is on 2D scanning, the project's inherent flexibility implies potential expandability or adaptation for more advanced applications. The open-source nature of the project encourages community contribution and further development, potentially leading to enhancements in data processing, visualization techniques, and even integration with other robotic or automation systems. The project aims to provide an accessible and affordable entry point into the world of LiDAR technology, empowering users to explore its capabilities and develop their own applications based on this foundational framework.

  • Raspberry Pi
  • LiDAR
  • Scanner
  • 3D Scanning
  • Robotics
  • Point Cloud
  • DIY
  • Hardware
  • Python
  • Sensor
  • SLAM
  • autonomous navigation
  • Laser Scanning

  Summary of Comments ( 158 )
  https://news.ycombinator.com/item?id=43738561

  Verbose tl;dr

  Hacker News users discussed the PiLiDAR project with a focus on its practicality and potential applications. Several commenters questioned the effective range and resolution of the lidar given the Raspberry Pi's processing power and the motor's speed, expressing skepticism about its usefulness for anything beyond very short-range scanning. Others were more optimistic, suggesting applications like indoor mapping, robotics projects, and 3D scanning of small objects. The cost-effectiveness of the project compared to dedicated lidar units was also a point of discussion, with some suggesting that readily available and more powerful lidar units might offer better value. A few users highlighted the educational value of the project, particularly for learning about lidar technology and interfacing hardware with the Raspberry Pi.

  The Hacker News post titled "Raspberry Pi Lidar Scanner" (linking to a GitHub project called PiLiDAR) has generated several comments, offering a variety of perspectives on the project.

  Several users discuss the practicality and applications of such a setup. One user highlights the potential limitations due to the Raspberry Pi's processing power, suggesting that a more powerful platform might be necessary for real-time, high-resolution scanning, especially with more advanced SLAM algorithms. They also express interest in the project's potential for robotics applications. Another user suggests the possibility of using it for indoor mapping and navigation, emphasizing the affordability of the setup. A different commenter points out the previous existence of similar projects using the Raspberry Pi and lidar, indicating this isn't an entirely novel concept.

  The discussion also touches upon the specific components used in the project. One comment mentions the RPLidar A1M8, a specific lidar model, and notes its limited range and resolution, suggesting alternative lidar units for improved performance depending on the desired application. This comment thread also delves into the cost-effectiveness of using the RPLidar A1 with a Raspberry Pi, considering other processing options. A separate comment chain discusses the intricacies of processing lidar data on resource-constrained devices like the Raspberry Pi, with suggestions for optimizing code and algorithms.

  Some comments focus on the software aspects. One user inquires about the specific SLAM algorithm being used and its suitability for the Raspberry Pi's hardware. Another user expresses interest in the project's potential for creating 3D models of environments. There's also mention of the project's use of Python and its libraries, with some users expressing appreciation for the language choice.

  A few comments touch upon the safety aspects of using lidar, particularly regarding eye safety and the power of the laser used.

  In summary, the comments section explores various facets of the project, including its technical feasibility, potential applications, component choices, software implementation, and safety considerations. The discussion reveals both enthusiasm for the project's potential and a pragmatic awareness of its limitations.

• Celestial Navigation for Drones

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  Posted: 2025-01-20 12:02:19

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  This paper explores the feasibility of using celestial navigation as a backup or primary navigation system for drones. Researchers developed an algorithm that identifies stars in daytime images captured by a drone-mounted camera, using a star catalog and sun position information. By matching observed star positions with known celestial coordinates, the algorithm estimates the drone's attitude. Experimental results using real-world flight data demonstrated the system's ability to determine attitude with reasonable accuracy, suggesting potential for celestial navigation as a reliable, independent navigation solution for drones, particularly in GPS-denied environments.

  This scholarly article, titled "Celestial Navigation for Drones: A Comprehensive Survey," delves into the intricate realm of employing celestial bodies for autonomous drone navigation, presenting a comprehensive overview of this emerging field. The authors meticulously examine the potential of using celestial cues, such as the positions of the sun, moon, and stars, as a robust and independent navigation solution for unmanned aerial vehicles (UAVs). They meticulously dissect the fundamental principles underlying celestial navigation, tracing its historical roots in maritime and aeronautical applications and meticulously translating these principles into the specific context of drone operation.

  The paper provides an exhaustive taxonomy of celestial navigation techniques applicable to drones, categorizing them based on the celestial body observed, the sensor technology employed, and the computational methods utilized. This detailed classification system facilitates a structured understanding of the diverse approaches to celestial navigation within the drone domain. A significant portion of the survey is devoted to an in-depth exploration of the various hardware components essential for celestial navigation in drones, including specialized cameras, star trackers, and attitude determination systems. Furthermore, the authors meticulously analyze the software algorithms required for processing celestial observations and converting them into actionable navigational data, including image processing techniques for star identification and filtering, as well as algorithms for attitude determination and position estimation.

  The article goes beyond merely describing existing techniques and delves into the inherent challenges and limitations associated with celestial navigation for drones. These include the adverse effects of atmospheric conditions, such as cloud cover and light pollution, on celestial observations, the intricacies of sensor calibration and alignment, and the computational demands of real-time processing of celestial data. The authors also address the crucial aspect of integrating celestial navigation with other navigation systems, such as GPS and inertial navigation, to enhance the overall reliability and robustness of drone navigation. This integrated approach leverages the strengths of each individual system while mitigating their respective weaknesses.

  Finally, the survey presents a forward-looking perspective on the future trajectory of celestial navigation for drones. It highlights promising research directions, including the development of novel sensor technologies, advanced algorithms for robust celestial observation processing, and innovative integration strategies with other navigation modalities. The authors posit the potential of celestial navigation to enable truly autonomous drone operations, particularly in GPS-denied environments or situations where enhanced navigational integrity is paramount, such as beyond visual line of sight (BVLOS) operations and critical infrastructure inspection. In conclusion, the paper offers a comprehensive and insightful exploration of celestial navigation for drones, serving as a valuable resource for researchers and practitioners alike, paving the way for future advancements in this burgeoning field.

  • drone navigation
  • celestial navigation
  • autonomous navigation
  • UAV
  • unmanned aerial vehicle
  • GNSS
  • GPS
  • alternative navigation
  • position estimation
  • attitude determination
  • star tracker
  • sensor fusion
  • aerospace engineering
  • Robotics

  Summary of Comments ( 37 )
  https://news.ycombinator.com/item?id=42767797

  Verbose tl;dr

  HN users discussed the practicality and novelty of the drone celestial navigation system described in the linked paper. Some questioned its robustness against cloud cover and the computational requirements for image processing on a drone. Others highlighted the potential for backup navigation in GPS-denied environments, particularly for military applications. Several commenters debated the actual novelty, pointing to existing star trackers and sextants used in maritime navigation, suggesting the drone implementation is more of an adaptation than a groundbreaking invention. The feasibility of achieving the claimed accuracy with the relatively small aperture of a drone-mounted camera was also a point of contention. Finally, there was discussion about alternative solutions like inertial navigation systems and the limitations of celestial navigation in certain environments, such as urban canyons.

  The Hacker News post titled "Celestial Navigation for Drones" links to a scientific paper detailing a method for drone navigation using celestial positioning. The comments section contains a moderate amount of discussion, primarily focusing on the practicality and limitations of the proposed method.

  Several commenters express skepticism about the real-world applicability of celestial navigation for drones, especially given the existing reliability and affordability of GPS. One commenter points out that GPS jamming and spoofing are already significant concerns, and while celestial navigation might offer a backup in these scenarios, the required clear sky conditions would often be unavailable precisely when such countermeasures are being employed. They also question the precision achievable with this method compared to GPS, particularly for small drones where minor positional errors could be significant.

  Another commenter highlights the computational complexity of celestial navigation, suggesting it would require significant processing power on the drone, potentially impacting battery life and payload capacity. They also mention the need for an extremely accurate clock, which adds further complexity and cost.

  A more supportive comment acknowledges the limitations but suggests the method could be valuable for specific niche applications where GPS is unavailable or unreliable, such as high-altitude or polar regions. They also propose a hybrid approach combining celestial navigation with other positioning systems for increased robustness.

  Some commenters discuss the potential benefits of using celestial navigation for security and resilience, arguing that it provides an independent and difficult-to-spoof navigation method. However, others counter that the vulnerability to cloud cover makes it less reliable in critical situations.

  One commenter raises the issue of light pollution, suggesting it could interfere with celestial navigation in urban environments. Another user mentions the potential for using a database of star positions to simplify the calculations, reducing the computational burden on the drone.

  A few commenters express interest in the historical context of celestial navigation and its potential resurgence in modern technology. They see the research as an interesting exploration of alternative navigation techniques, even if the practical applications are limited.

  Overall, the comments reflect a mixed reception to the idea of celestial navigation for drones. While some see potential in specific niche applications, many remain skeptical about its widespread adoption due to the limitations and challenges compared to existing GPS technology. The discussion highlights the trade-offs between resilience, accuracy, complexity, and cost associated with different navigation methods.