Distributed pursuit-evasion without mapping or global localization via local frontiers

Abstract

This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available

Modeling and Control of UAV Bearing Formations with Bilateral High-level Steering

“…Figure 12 represents the plane spanned by the points p l , p m , p n . From the law of sines, it follows δ ln δ lm = sin(∆ ln ) sin(∆ lm ) , where sin(∆ ln ) = β mn × β ml and sin(∆ lm ) = β nl × β nm = l R n β nl × l R n β nm = = − β ln × l R m m R n β nm , thus proving (9). Finally, (10) follows from (8) , where the denominator p n − p m δ −1 lm = β ln γ lmn − β lm since β mn is a unit vector.…”

“…This way, the controller is independent of the knowledge of the robot absolute positions in space and, thus, does not require presence of global localization systems such as GPS or SLAM algorithms (see, e.g., [9]). In the same spirit, A. Franchi, C. Masone, V. Grabe substantial research efforts have been devoted to the development of solutions based on standard, light-weight, lowenergy, and cheap sensors (like onboard cameras), rather than active and energetically-expensive sensing devices (like, e.g., laser/structured-light range-sensors) [3].…”

A passivity-based decentralized strategy for generalized connectivity maintenance

“…In fact, these can be usually obtained from direct onboard sensing, and are thus free from the presence of global localization modules such as GPS or simultaneous localization and mapping (SLAM) algorithms (see, e.g., Durham et al, 2012), or other forms of centralized…”

Moving From ‘How to go There?’ to ‘Where to go?’: Towards Increased Autonomy of Mobile Robots

“…They have been selected only based on the expertise of the authors and are not intended to endorse any claim of generality or importance. Other examples include continuous monitoring of temporal-spatial phenomena in partially known environments (e.g., ocean monitoring [28]), olfactory exploration [22], tactile exploration of object properties [25], information gathering [27], and pursuit/evasion [13].…”