Image-Based Mobile Robot Guidance System by Using Artificial Ceiling Landmarks

This paper presents an image-based mobile robot guidance system in an indoor space with installed artificial ceiling landmarks. The overall system, including an omni-directional mobile robot motion control, landmark image processing and image recognition, is implemented on a single FPGA chip with one CMOS image sensor. The proposed feature representation of the artificial ceiling landmarks is invariant with respect to rotation and translation. One unique feature of the proposed ceiling landmark recognition system is that the feature points of landmarks are determined by topological information from both the foreground and background. To enhance recognition accuracy, landmark classification is performed after the mobile robot is moved to a position such that the ceiling landmark is located in the upright- top corner position of the robot’s camera image. The accuracy of the proposed artificial ceiling landmark recognition system using the nearest neighbor classification is 100% in our experiments.

Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene

The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability.Localization of mobile robot is increasingly important for the printing of buildings in the construction scene.Although many available studies on the localization have been conducted,only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes.To realize the accurate localization of mobile robot in designated stations,we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole map.Then,the performances of localization for mobile robot based on the original and optimized map are compared and evaluated.Finally,experimental results show that the average absolute localization errors that adopted the proposed algorithm is reduced by about 21%compared to that of the original map.

Localization and navigation using a novel artificial landmark for indoor mobile robots

This paper presents a practical topological navigation system for indoor mobile robots, making use of a novel artificial landmark which is called MR code. This new kind of paper-made landmarks earl be easi- ly attached on the ceilings or on the walls, lmealization algorithms for the two cases are given respective- ly. A docking control algorithm is also described, which a robot employs to approach its current goal. A simple topological navigation algorithm is proposed. Experiment results show the effectiveness of the method in real environment.

Simultaneous Localization and Mapping System Based on Labels

In this paper a label-based simultaneous localization and mapping（ SLAM） system is proposed to provide localization to indoor autonomous robots. In the system quick response（ QR） codes encoded with serial numbers are utilized as labels. These labels are captured by two webcams,then the distances and angles between the labels and webcams are computed. Motion estimated from the two rear wheel encoders is adjusted by observing QR codes. Our system uses the extended Kalman filter（ EKF） for the back-end state estimation. The number of deployed labels controls the state estimation dimension. The label-based EKF-SLAM system eliminates complicated processes,such as data association and loop closure detection in traditional feature-based visual SLAM systems. Our experiments include software-simulation and robot-platform test in a real environment. Results demonstrate that the system has the capability of correcting accumulated errors of dead reckoning and therefore has the advantage of superior precision.

Distributed environment representation and object localization system in intelligent space

A kind of new environment representation and object localization scheme is proposed in the paper aiming to accomplish the task of object operation more efficiently in intelligent space. First, a distributed environment represen- tation method is put forward to reduce storage burden and improve the system＇s stability. The layered topological maps are separately stored in different landmarks attached to the key positions of intelligent space, so that the robot can search the landmarks on which the map information can be read from the QR code, and then the environment map can be built autonomously. Map building is an important prerequisite for object search. An object search scheme based on RFID and vision technology is proposed. The RFID tags are attached to the target objects and reference objects in the indoor environ- ment. A fixed RFID system is built to monitor the rough position （room and local area） of target and a mobile RFID system is constructed to detect the targets which are not in the covering range of the fixed system. The existing area of target is determined by the time sequence of reference tags and target tags, and the accurate position is obtained by onboard vision system at a short distance. The experiments demonstrate that the distributed environment representation proposed in the paper can fully meet the requirements of object localization, and the positioning scheme has high search efficiency, high localization accuracy and precision, and a strong anti-interference ability in the complex indoor environment.