Scale-free vision-based aerial control of a ground formation with hybrid topology

We present a novel vision-based control method to make a group of ground mobile robots achieve a specified formation shape with unspecified size. Our approach uses multiple aerial control units equipped with downward-facing cameras, each observing a partial subset of the multirobot team. The units compute the control commands from the ground robots' image projections, using neither calibration nor scene scale information, and transmit them to the robots. The control strategy relies on the calculation of image similarity transformations, and we show it to be asymptotically stable if the overlaps between the subsets of controlled robots satisfy certain conditions. The presence of the supervisory units, which coordinate their motions to guarantee a correct control performance, gives rise to a hybrid system topology. All in all, the proposed system provides relevant practical advantages in simplicity and flexibility. Within the problem of controlling a team shape, our contribution lies in addressing several simultaneous challenges: the controller needs only partial information of the robotic group, does not use distance measurements or global reference frames, is designed for unicycle agents, and can accommodate topology changes. We present illustrative simulation results.Comment: This is the accepted version an already published manuscript. See journal reference for detail

ADAPTIVE IMAGE ENHANCEMENT MODEL FOR THE ROBOT VISION SYSTEM

Robotics is one of the important trends in the current development of science and technology. Most modern robots and drones have their own vision system, including a video camera, which they use to take digital photos and video streams. These data are used to analyze the situation in the robot's camera field of view, as well as to determine a real-time robot's behavior algorithm. In this regard, the novelty of the paper is special polynomial mathematical model and method for adaptive gradational correction of a digital image. The proposed model and method make it possible to independently adjust to brightness scales and image formats and optimally perform gradational image correction in various lighting conditions. Thus, ensuring the efficiency of the entire subsequent cycle of image analysis in the robot's vision system. In addition, the paper presents the results of numerous experiments of such gradational correction for images of various classes, as well as conditions of reduced and increased levels of illumination of the field of view objects. Conclusions and recommendations are given regarding the practical application of the proposed model and method

Scale-Free Vision-Based Aerial Control of a Ground Formation With Hybrid Topology

International audienc