Human Detection Method by 3D-LiDAR with Low Calculation Costs

Abstract

Since the COVID-19 pandemic, Japanese industry has been facing a labor shortage in various fields. The security sector, in particular, has a severe labor shortage due to the harsh working environment, which involves working early in the morning, at night, and outdoors. Due to the effects of COVID-19, facilities have been closed, price competition among security companies has also had an impact, and salaries are low and career development is difficult. Even in relatively open spaces such as university campuses, patrols are necessary from a safety perspective. University security operations are also being affected by the lack of security guards. Therefore, it is necessary to reduce the patrol duties of security guards as much as possible. They should patrol frequently, especially at night, and it is effective to have robot carts patrol. Robot technology is developing and it is becoming possible to perform not only simple tasks but also tasks that involve interaction with humans. In particular, robots are expected to be introduced in patrol security, which requires a large number of personnel, as much of the work involves confirming that there are no problems. In Japan, for example, robots that serve food at restaurants move around in the flow of people . In terms of security, if it cannot be confirmed by robots that there is no problem, a security guard is required to go and check. In order to reduce such cases, improving the accuracy of confirmation is an absolute requirement. In addition, it is necessary to reduce the cost of introducing and operating the robot as much as possible. Technology for recognizing people using cameras mounted on robots and 3D-LiDAR(Light Detection And Raging) has already been established and is in use. However, no technology has been established for use in poorly lit areas or by low-cost 2D-LiDAR recognition. Several methods were proposed for recognizing people using 2D-LiDAR. However, there were some conditions and problems with accuracy. In this paper, we propose a method for human identification that utilizes only limited information from the point cloud information obtained by 3D-LiDAR. Specifically, when it finds information that differs from the background information, it determines the possibility of a human being based on the distance, and improves its accuracy by moving the robot closer. Criminals and other malicious people will flee. If this is not the case, by notifying the office, it can be used to call out remotely. We have evaluated our method from some aspects which are distance between robots and humans, number of pointcloud data. As a result, we show that by setting appropriate parameters, it is possible to make accurate detection.

Keywords: Robot, LiDAR, Human detection

DOI: 10.54941/ahfe1005512