AINS: Affordable Indoor Navigation Solution via Line Color Identification Using Mono-Camera for Autonomous Vehicles
Recently, researchers have been exploring various ways to improve the effectiveness and efficiency of autonomous vehicles by researching new methods, especially for indoor scenarios. Autonomous Vehicles in indoor navigation systems possess many challenges especially the limited accuracy of GPS in indoor scenarios. Several, robust methods have been explored for autonomous vehicles in indoor scenarios to solve this problem, but the ineffectiveness of the proposed methods is the high deployment cost. To address the above-mentioned problems we have presented A low-cost indoor navigation method for autonomous vehicles called Affordable Indoor Navigation Solution (AINS) which is based on based on Monocular Camera. Our proposed solution is mainly based on a mono camera without relying on various huge or power-inefficient sensors to find the path, such as range finders and other navigation sensors. Our proposed method shows that we can deploy autonomous vehicles indoor navigation systems while taking into consideration the cost. We can observe that the results shown by our solution are better than existing solutions and we can reduce the estimated error and time consumption.
Code (0)
등록된 구현이 없습니다.
Tasks
Autonomous VehiclesMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops
Expensive sensors and inefficient algorithmic pipelines significantly affect the overall cost of autonomous machines. However, affordable robotic solutions are essential to practical usage, and their financial impact con…
Autonomous NavigationLLM-Guided Agentic Floor Plan Parsing for Accessible Indoor Navigation of Blind and Low-Vision People
Indoor navigation remains a critical accessibility challenge for the blind and low-vision (BLV) individuals, as existing solutions rely on costly per-building infrastructure. We present an agentic framework that converts…
Grid2Guide: A* Enabled Small Language Model for Indoor Navigation
Reliable indoor navigation remains a significant challenge in complex environments, particularly where external positioning signals and dedicated infrastructures are unavailable. This research presents Grid2Guide, a hybr…
AI and Machine Learning Driven Indoor Localization and Navigation with Mobile Embedded Systems
Indoor navigation is a foundational technology to assist the tracking and localization of humans, autonomous vehicles, drones, and robots in indoor spaces. Due to the lack of penetration of GPS signals in buildings, subt…
Autonomous VehiclesIndoor LocalizationNavVerse: Benchmarking Indoor-to-Outdoor Embodied Navigation in Continuous Robot Simulation
Robots deployed in delivery, campus, and emergency-response settings often need to navigate from buildings to streets within a single continuous episode. Existing benchmarks usually evaluate indoor and outdoor navigation…