Jose Joaquin Acevedo

Cooperative Large Area Surveillance with a Team of Aerial Mobile Robots for Long Endurance Missions

This paper proposes a distributed approach to solve long duration area surveillance missions with a team of aerial robots, taking into account communication constraints. The system, based on “one-to-one” coordination, minimizes the probability that any event happens in the area without being detected and ensures periodic communication between UAVs. A set of simulations are presented to validate the applicability of the approach and its most relevant features: convergence, robustness with dynamic teams, fault-tolerance and finite information sharing time. It is also shown that “one-to-one” coordination for all the pairs of neighbors allows to obtain an efficient coordination scheme for the whole team to accomplish the area surveillance mission without any central unit.

Distributed Approach for Coverage and Patrolling Missions with a Team of Heterogeneous Aerial Robots Under Communication Constraints

Using aerial robots in area coverage applications is an emerging topic. These applications need a coverage path planning algorithm and a coordinated patrolling plan. This paper proposes a distributed approach to coordinate a team of heterogeneous UAVs cooperating efficiently in patrolling missions around irregular areas, with low communication ranges and memory storage requirements. Hence it can be used with small-scale UAVs with limited and different capabilities. The presented system uses a modular architecture and solves the problem by dividing the area between all the robots according to their capabilities. Each aerial robot performs a decomposition based algorithm to create covering paths and a ‘one-to-one’ coordination strategy to decide the path segment to patrol. The system is decentralized and fault-tolerant. It ensures a finite time to share information between all the robots and guarantees convergence to the desired steady state, based on the maximal minimum frequency criteria. A set of simulations with a team of quad-rotors is used to validate the approach.

One-to-One Coordination Algorithm for Decentralized Area Partition in Surveillance Missions with a Team of Aerial Robots

This paper presents a decentralized algorithm for area partition in surveillance missions that ensures information propagation among all the robots in the team. The robots have short communication ranges compared to the size of the area to be covered, so a distributed one-to-one coordination schema has been adopted. The goal of the team is to minimize the elapsed time between two consecutive observations of any point in the area. A grid-shape area partition strategy has been designed to guarantee that the information gathered by any robot is shared among all the members of the team. The whole proposed decentralized strategy has been simulated in an urban scenario to confirm that fulfils all the goals and requirements and has been also compared to other strategies.

Cooperative perimeter surveillance with a team of mobile robots under communication constraints

This paper presents the perimeter surveillance problem using a set of cooperative robots with heterogeneous speed capabilities under communication constraints. The problem is solved using a frequency-based approach. In the proposed path-partition strategy, the robots patrol a segment length related to their own capabilities and interchanges information with its neighbors periodically. An efficient decentralized algorithm is applied to coordinate the robots from local information and decisions. Finally, simulation and experimental results are presented to illustrate the convergence and the robustness of the solution.

Decentralized strategy to ensure information propagation in area monitoring missions with a team of UAVs under limited communications

This paper presents the decentralized strategy followed to ensure information propagation in area monitoring missions with a fleet of heterogeneous UAVs with limited communication range. The goal of the team is to detect pollution sources over a large area as soon as possible. Hence the elapsed time between two consecutive visits should be minimized. On the other hand, in order to exploit the capabilities derived from having a fleet of UAVs, an efficient area partition is performed in a distributed manner using a one-to-one coordination schema according to the limited communication ranges. Another requirement is to have the whole team informed about the location of the new pollution sources detected. This requirement is challenging because the communication range of the vehicles is small compared to the area covered in the mission. Sufficient and necessary conditions are provided to guarantee one-to-one UAV communication in grid-shape area partitions, allowing to share any new information among all the members of the team, even under strong communication constraints. The proposed decentralized strategy has been simulated to confirm that fulfils all the goals and requirements and has been also compared to other patrolling strategies.

The block-sharing strategy for area monitoring missions using a decentralized multi-UAV system

In monitoring missions, using a cooperative team of Unmanned Aerial Vehicles (UAVs), the goal is to minimize the elapsed time between two consecutive observations of any point in the area. Techniques based in area partitioning achieve the goal when the sub-area assigned to each UAV is according to its capabilities. In previous work of the authors [1] it was presented the one-to-one strategy to obtain in a decentralized way a near optimal partition from any initial grid partition. In this paper a generalization of that strategy called the block-sharing technique is presented. The goal in this work is to accelerate the convergence to an optimal partition with respect to previous work.

A decentralized algorithm for area surveillance missions using a team of aerial robots with different sensing capabilities

This paper addresses the area surveillance problem with a team of multiple aerial robots under communication constraints. In previous work of authors [1], a decentralized modular architecture was proposed for surveillance missions with a team of homogeneous robots. This paper presents a decentralized decision-making algorithm that solves the problem for heterogeneous aerial robots with different sensing and motion capabilities. The proposed frequency-based approach offers a dynamic and robust solution able to adapt to changes in the area size and robot capabilities, and even to total robot failures. The algorithm can run properly under communication constraints and there is no robot which rules the others. Simulations and experimental results validate the proposed system for heterogeneous robots that can be dynamically added/removed during the execution of the mission.

Cooperative Perimeter Surveillance Using Aerial Robots and Fixed Ground Stations

This paper addresses the problem of border surveillance with aerial robots and ground stations considering prioritized zones. Based on a frequency-based approach and these priorities, a metric called urgency is defined to normalize all the zones and analyze how well the whole perimeter is monitored. Assuming that a ground station divides the whole border in different zones with different lengths and different priorities, a fully decentralized system is designed to minimize the urgency along the whole perimeter. An algorithm based on coordination variables is applied to compute the path partitioning strategy along each zone for the cooperation of the aerial robots. One-to-one coordination is used to solve the exchanging zones problem in a distributed manner. By exchanging zones the aerial robots enhance the full system performance following the urgency-criteria. System features and modifications to the main algorithm are analyzed and tested in different simulations.

A distributed framework for surveillance missions with aerial robots including dynamic assignment of the detected intruders

A dynamic and decentralized assignment algorithm based on one-to-one coordination is proposed to solve the multi-target allocation problem under communication constraints. The objective is to assign the intruders dynamically among the available aerial robots in order to keep as many intruders as possible under tracking. When an aerial robot is not tracking a target, it is patrolling the area in order to detect new intruders. The proposed distributed method has been implemented and tested both in simulation and in an indoor testbed with quadrotors in order to validate its interest in dynamic scenarios with multiple intruders and multiple aerial robots. Comparisons with centralized assignment methods are provided to show the algorithm performance.

Visual Surveillance System with Multi-UAVs Under Communication Constrains

In this paper, it is proposed a visual surveillance system for multiple UAVs under communication constrains. In previous works, a dynamic task allocation algorithm was designed for assigning patrolling and tracking tasks between multiple robots. The idea was to assign the intruders dynamically among the robots using one-to-one coordination technique. However due to communication constrains, every UAVs could store different information. In this paper, local information about targets is obtained by a visual algorithm that detects moving objects during surveillance tasks using fixed low-cost monocular RGB-camera connected to an on-board computer. This system was tested in a urban surveillance scenario, implemented in an indoor test-bed, under EC-SAFEMOBIL project.