Efficient and secure real-time mobile robots cooperation using visual servoing

Abstract

This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. In addition, in case of problem, a robot accident detection reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method.

Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review

“…More precisely, Table 1 lists the vision-based approaches with their contributions, sensors, and real-time performance, and the most popular method is the optic flow, which is used by bees. The vision-based applications include transport [ 9 , 18 , 39 , 46 , 50 , 60 ], exploration [ 8 , 19 , 24 , 26 , 40 , 41 , 45 , 49 ], tracking and assist [ 31 , 56 , 58 ], security and surveillance [ 7 , 52 ], homing and searching [ 5 , 54 , 55 ], floor cleaning [ 6 , 43 ], and search and rescue [ 44 ]. Only 43.75% of the cited papers indicate they can operate in real time, which is achieved by processing or computation speed, minimal computation load, or predefined parameters.…”

“…Boudra et al [ 56 ] introduced a mobile robot’s cooperation and navigation based on visual servoing, which controlled the angular and linear velocities of the multiple robots. The interaction matrix was developed to combine the images with velocities and estimate the depth of the target and each robot, although it could not be applied to 3D parameters.…”

Intelligent machine for sorting semi-precious minerals

“…This restriction is acceptable for sorting fruits, but not acceptable for precious and semi-precious minerals due to the low accuracy of sorting. For example, in agriculture, a promising area for product sorting systems is the use of mobile robots [15], [16] as actuators. But unfortunately, these robots are in lack of optical recognition systems.…”