Zhang Tan, Chen Chao. Guiding the blind to overcome environment limitation[J]. Journal of Image and Graphics, 2015, 20(11): 1545-1551.DOI: 10.11834/jig.20151114.
Guiding the blind to overcome environment limitation
the total number of the visually handicapped in the world is large and continues to grow. However
most seeing-eye robots are limited to the specific environment or single spaces and have difficulty adapting to changes in environment. Thus
these robots lack practical value to meet the needs of society. To overcome the space limitation and guide the blind in different environments
this paper proposes an effective method for guiding the blind based on the creation of environmental maps to expand the scope of the environmental adaptation of the seeing-eye robot. First of all
simultaneous localization and mapping (SLAM) is used to create a two-dimensional map of the environment
in which the seeing-eye robot localize itself and simultaneously build an environmental map based on observational features and position estimation;Then
the A heuristic search algorithm is used to plan a global path to find an optimal path without collision in the static map that has been created. The artificial potential field algorithm is then combined to avoid the dynamic obstacles detected by the seeing-eye robot when walking along the global path;Finally
the software control system of the seeing-eye robot is constructed using the robot operating system (ROS) framework so that the functional nodes can communicate with each other to obtain the required data based on certain rules
thereby making the whole control system more orderly and efficient. The experiments were carried out in three typical surroundings
such as an office
a long corridor of big building
and an outdoor rest area. The result of the experiments proved that
compared with other blind methods
the proposed method is applicable to a wider range and more flexible environment and is no longer limited to a single space or specific environment. In the process of creating the map
the feature estimated error is only within the range of 5cm-35cm when the total number of features is 30 and the position estimated error is less than 3m when the walking steps are up to 12000 steps. In planning the path
trajectory error is under 0.4m when the length is up to 120m. By comparison
the proposed method is more practical and superior for guiding the blind. This paper presents a method for guiding the blind applicable to various environments. The corresponding experimental results demonstrate that the map created by the method is consistent with the actual scene and the trajectory of the robot is essentially identical to the planned path in various environments
so its precision is relatively high. The method is generally applicable to indoor and outdoor areas of the daily activities of the visually handicapped and the method is sufficiently flexible to adapt to transformation in the environment. Therefore the method proposed by this paper is more practical and effective for guiding the blind.
Artificial Intelligence Research Institute, Wuhan University
GNSS Center, Wuhan University
College of Mechanical and Electrical Engineering, Jiaxing University
南京理工大学计算机系
Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Department of Computer Science and Technology, Beijing University of Technology