Farid Sharifi

Fault tolerant control of a quadrotor UAV using sliding mode control

In this paper, the sliding mode approach is used to control of a quadrotor unmanned aerial vehicle (UAV) in the presence of external disturbance and actuator fault. Fault detection unit can detect the actuator fault using a state estimator. Then it reconfigures the structure of controller such that some control performance is achieved. The proposed control structure has the advantage of disturbance rejection in the fault-free condition. Moreover it can recover some of control performances when a fault occurs. Different simulations have been carried out to show the performance and effectiveness of the proposed method.

A Distributed Deployment Strategy for a Network of Cooperative Autonomous Vehicles

This brief presents a distributed deployment algorithm for a network of heterogeneous mobile agents to minimize a prescribed cost function. This function is concerned with the cost of serving the entire field by all agents, where the so called operation cost of different agents are not necessarily the same. The problem is investigated for the case where agents have different types of dynamics. Using a multiplicatively-weighted Voronoi diagram, the field is partitioned to smaller regions (one for each agent). A distributed coverage control law is then provided that guarantees the convergence of agents to the optimal configuration with respect to the above-mentioned cost function. The effectiveness of the proposed algorithm is demonstrated by simulations and experiments on a testbed with two types of unmanned vehicles (aerial and ground).

Cooperative multi-vehicle search and coverage problem in uncertain environments

A decentralized approach is proposed to solve a cooperative multi-vehicle search and coverage problem in uncertain environments. Two different types of vehicle are used for search and coverage tasks. The search vehicles have a priori probability maps of targets in the environment and they update these maps based on the measurement of their sensors during the search mission. They use a limited look-ahead dynamic programming algorithm to find their own path individually while their objective is to maximize the amount of information gathered by the whole team. The task of service vehicles is to spread out over the environment to optimally cover the terrain. A locational optimization technique is used to assign Voronoi regions to vehicles and the stability of coverage system is guaranteed using LaSalles invariance principle. The service vehicles modify their configuration using the updated probability maps which are provided by the search vehicles. Simulations show that the proposed approach offers improved performance compared to conventional coverage methods.

Distributed coordination of multi-agent systems for coverage problem in presence of obstacles

This paper presents new algorithms for distributed deployment of a network of multi-agent systems to minimize prescribed cost function. It is assumed that the so-called “operation cost” of distinct agents can be different. The problem is investigated for both cases of an obstacle-free environment and a fixed-obstacle environment. For the former case, the center multiplicatively weighted Voronoi (CMWV) configuration is introduced, and it is shown to be the optimal configuration. A distributed coverage control is also provided which guarantees that the configuration of the agents converges to this optimal configuration. For the case of a fixed-obstacle environment, the visibility-aware multiplicatively weighted Voronoi (VMW-Voronoi) diagram is introduced and a motion coordination strategy is presented to achieve the desired objective. Simulations demonstrate the effectiveness of the proposed algorithms in both cases.

Cooperative multi-vehicle search and coverage problem in an uncertain environment

A distributed approach is proposed in this paper to address a cooperative multi-vehicle search and coverage problem in an uncertain environment such as forest fires monitoring and detection. Two different types of vehicles are used for search and coverage tasks: search and service vehicles. The search vehicles have a priori probability maps of targets in the environment. These vehicles update the probability maps based on their sensors measurements during the search mission. The search vehicles use a limited look-ahead dynamic programming algorithm to find their own path individually while their objective is to maximize the amount of information gathered by the whole team. The task of the service vehicles is to optimally spread out over the environment to cover the interested area for a mission. A Voronoi-based coverage control strategy is proposed to modify the configuration of service vehicles in such a way that a prescribed coverage cost function is minimized using the updated probability maps which are provided by the search vehicles. The improved performance of the proposed approach compared to conventional coverage methods is demonstrated by numerical simulation and experimental results. Language: en

A Distributed Deployment Strategy for Multi-Agent Systems Subject to Health Degradation and Communication Delays

This paper presents a distributed deployment algorithm for a network of autonomous agents. The main goal is to perform a coverage task when the sensor effectiveness of each agent varies during the mission. It is also assumed that the agents are subject to communication delays induced by communication faults. To improve the overall performance and guarantee the collision avoidance, the guaranteed multiplicatively-weighted Voronoi (GMW-Voronoi) diagram is introduced. A distributed coverage control is then provided to drive agents in such a way that the coverage performance function is minimized over the regions assigned to agents. The effectiveness of the proposed algorithm is evaluated by simulations.

Cooperative Multi-UAV Search Problem with Communication Delay

This paper is concerned with a cooperative multi-UAV search problem with communication delay in an uncertain environment. A decentralized decision making approach is proposed to solve the problem. Each vehicle uses a limited look-ahead dynamic programming (DP) algorithm to find its own path. The vehicles share their location and sensor information with each other. However, due to limitations in communication bandwidth, the vehicles are not able to negotiate with each other about their actions. In order to allow cooperation between the vehicles despite such constraints, a stochastic method is proposed to estimate the probability of the different actions for all vehicles. The objective function of each vehicle is modified such that it considers the influence of the different actions of the other vehicles in the team on its own decisions. A similar method is utilized to compensate for the impact of communication delays between the vehicles on mission performance. Finally, these two methods are combined and a general method is introduced to enable cooperation among vehicles in the presence of communication delays. Simulations show that the proposed approach offers improved performance compared to existing approaches.

Decentralized Sliding Control of Cooperative Multi-Agent Systems Subject to Communication Delays

This paper investigates decentralized sliding mode control (SMC) of multi-agent cooperative systems when the inter-agent communication delay cannot be neglected. A new algorithm is proposed to control and maintain the cooperation objectives when large communication delays occur due to faulty network conditions. The faulty agents perform prediction of all other agents in order to perform decentralized SMC. An upper bound is also derived for the state prediction error. The new approach is applied to formation control of a group of wheeled mobile robots. Simulation results show that the proposed approach has good performance and stability properties for cases with large delay compared to centralized SMC.

Coverage control in multi-vehicle systems subject to health degradation

This paper presents a distributed deployment algorithm for a network of multi-vehicle systems to minimize a prescribed cost function. The goal is to perform a coverage task when the capability of the vehicles to carry out the task varies through time. The problem is investigated for the case where vehicles have variable sensing performance. A specific partitioning technique is used to address this problem, and optimal configuration for vehicles is also introduced. A distributed coverage control is then provided which guarantees the convergence of vehicles to the best configuration subject to health degradation due to faults in individual vehicle of the team. The effectiveness of the proposed algorithms is demonstrated by numerical simulations.

A Coverage Strategy with Guaranteed Collision Avoidance in Multi-Agent Systems using Navigation Functions

A distributed navigation-function-based controller is proposed to solve a cooperative multi-agent coverage problem. The field is partitioned to the Voronoi cells first. A control strategy is subsequently proposed to relocate the agents in such a way that a prescribed coverage cost function is minimized while collision and obstacle avoidance are guaranteed. The convergence analysis is provided to show the stability of the network under the proposed control strategy. Simulations demonstrate the effectiveness of the results.