45 International Journal of Engineering and Science Applications Vol 8 No. 2 November 2021 ISSN 2406-9833 IJEScA Cooperative Observation with Prediction Of Targets Position Moving Over A Fully Observable Planar Graph J E B Maia* and L P Figueiredo, Universidade Estadual do Ceará - Brasil. *Email: jose.maia@uece.br (correspondence author). ABSTRACT Consider a team with two types of agents: targets and observers. Observers are aerial UAVs that observe targets moving on land with their movements restricted to the paths that form a planar graph on the surface. Observers have limited range of vision and targets do not avoid observers. The objective is to maximize the integral of the number of targets observed in the observation interval. Taking advantage of the fact that the future positions of targets in the short term are predictable, we show in this article a modified hill climbing algorithm that surpasses its previous versions in this new setting of the CTO problem. Keywords: Cooperative targets observation, Multivalent control, Motion over a planar graph, K- means. 1. INTRODUCTION Unmanned vehicles (UAVs), whether terrestrial, aquatic or aerial, such as drones, already accumulate a variety in civil applications or military defense and attack. Civil applications include environmental monitoring [1], medical assistance [2], transport of goods [3], electronic surveillance [4], and aerial data surveys using photogrammetry techniques or LIDAR [5, 6] sensors. Military applications of UAVs already reported include mission of attack [7], defense against attacks by other UAVs [8], [9], [10], reconnaissance [11] and border surveillance [12]. UAVs are a type of agents suitable for use as observers. The Cooperative Target Observation (CTO) problem domain is one in which a team of moving surveillance robots, for example, drones, must maintain the observation of another target robot team in motion, in order to maximize the Average Number of Observed Targets (ANOT ) in the period. The CTO problem domain has a variety of instances depending on the type of movement of the targets, resource constraints, the interaction between targets and observers, and the stated specific objective. The survey in [13] presents a classification of problems related to CTO. In this paper, a new setting and algorithm for the cooperative targets observation problem is presented. In the configuration faced in this work the targets move on a planar graph and their future positions can be predicted. For a concrete example, consider an urban scenario in which N aerial UAVs, each with limited observation radius R, must patrol M > N targets moving on land. The movement of the UAVs is free while the movement of targets is restricted to certain paths, such as urban roads. Targets are friends who can, for example, be attacked by enemies. In this scenario, it can be assumed that the positions of the targets and the observers, obtained from GPS, are transmitted to a central command, and that the