Mixed marker-based/marker-less visual odometry system for mobile robots

When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental test

Virtual Borders: Accurate Definition of a Mobile Robot's Workspace Using Augmented Reality

We address the problem of interactively controlling the workspace of a mobile robot to ensure a human-aware navigation. This is especially of relevance for non-expert users living in human-robot shared spaces, e.g. home environments, since they want to keep the control of their mobile robots, such as vacuum cleaning or companion robots. Therefore, we introduce virtual borders that are respected by a robot while performing its tasks. For this purpose, we employ a RGB-D Google Tango tablet as human-robot interface in combination with an augmented reality application to flexibly define virtual borders. We evaluated our system with 15 non-expert users concerning accuracy, teaching time and correctness and compared the results with other baseline methods based on visual markers and a laser pointer. The experimental results show that our method features an equally high accuracy while reducing the teaching time significantly compared to the baseline methods. This holds for different border lengths, shapes and variations in the teaching process. Finally, we demonstrated the correctness of the approach, i.e. the mobile robot changes its navigational behavior according to the user-defined virtual borders.Comment: Accepted on 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), supplementary video: https://youtu.be/oQO8sQ0JBR

MOMA: Visual Mobile Marker Odometry

In this paper, we present a cooperative odometry scheme based on the detection of mobile markers in line with the idea of cooperative positioning for multiple robots [1]. To this end, we introduce a simple optimization scheme that realizes visual mobile marker odometry via accurate fixed marker-based camera positioning and analyse the characteristics of errors inherent to the method compared to classical fixed marker-based navigation and visual odometry. In addition, we provide a specific UAV-UGV configuration that allows for continuous movements of the UAV without doing stops and a minimal caterpillar-like configuration that works with one UGV alone. Finally, we present a real-world implementation and evaluation for the proposed UAV-UGV configuration

Performance Study on Natural Marker Detection for Augmented Reality Supported Facility Maintenance

The operation and maintenance phase is the longest and most expensive life-cycle period of building facilities. Operators need to perform activities to provide a comfortable living and working environment and to upkeep equipment to prevent functionality failures. For that purpose they manually browse, sort and select dispersed and unformatted facility information before actually going on the site. Although some software tools have been introduced, they still spent 50% of the on-site work on inspection target localization and navigation. To improve these manual, time consuming and tedious procedures, the authors previously presented a framework that uses BIM-based Augmented Reality (AR) to support facility maintenance tasks. The proposed workflow contains AR supported activities, namely AR-based indoor navigation and AR-based maintenance instructions. An inherent problem of AR is marker definition and detection. As introduced, indoor natural markers such as exit signs, fire extinguisher location signs, and appliances’ labels were identified to be suitable for both navigation and maintenance instructions. However, small markers, changing lighting conditions, low detection frame rates and accuracies might prevent the proposed approach from being practical. In this paper the performance of natural marker detection will be evaluated under different configurations, varying marker types, marker sizes, camera resolutions and lighting conditions. The detection performance will be measured using pre-defined metrics incorporating detection accuracy, tracking quality, frame rates, and robustness. The result will be a set of recommendations on what configurations are most suitable and practical within the given framework

AUGMENTED REALITY BASED INDOOR POSITIONING NAVIGATION TOOL.

Nowadays, indoor navigation gained people’s attention. Lots of techniques and technologies have been used in order to develop the indoor navigation. Indoor navigation is far away behind the outdoor navigation. For outdoor navigation, we have GPS to guide and give direction to the desired place. Unfortunately, it is restricted for the outdoor purpose only. Thus, the main objective of this project is to develop an interactive indoor navigation system and augmented reality is being use to superimposed the directional signage. In this project small computer which is Raspberry Pi has been used as a computing device. Probably in the future, all smartphones will have augmented reality based indoor navigation tools because it already equipped with many sensors such as an accelerometer, gyro, and compass which will improve the accuracy of positioning. Basically, the project has been tested at Universiti Teknologi PETRONAS’s Information Resource Centre (IRC), and it has shown its flexibility in working as an indoor positioning tool to navigate to 5 different locations with multiple levels

Use of Augmented Reality in Human Wayfinding: A Systematic Review

Augmented reality technology has emerged as a promising solution to assist with wayfinding difficulties, bridging the gap between obtaining navigational assistance and maintaining an awareness of one's real-world surroundings. This article presents a systematic review of research literature related to AR navigation technologies. An in-depth analysis of 65 salient studies was conducted, addressing four main research topics: 1) current state-of-the-art of AR navigational assistance technologies, 2) user experiences with these technologies, 3) the effect of AR on human wayfinding performance, and 4) impacts of AR on human navigational cognition. Notably, studies demonstrate that AR can decrease cognitive load and improve cognitive map development, in contrast to traditional guidance modalities. However, findings regarding wayfinding performance and user experience were mixed. Some studies suggest little impact of AR on improving outdoor navigational performance, and certain information modalities may be distracting and ineffective. This article discusses these nuances in detail, supporting the conclusion that AR holds great potential in enhancing wayfinding by providing enriched navigational cues, interactive experiences, and improved situational awareness.Comment: 52 page

Augmented Reality Based Indoor Positioning Navigation Tool

The main objective of this project is to design a new method to develop indoor positioning navigation system without using wireless technology through image processing