arpita sinha - Academia.edu (original) (raw)

Papers by arpita sinha

European Journal of Control, 2009

Abstract One of the major tasks in swarm intelligence is to design decentralized but homogenoeus ... more Abstract One of the major tasks in swarm intelligence is to design decentralized but homogenoeus strategies to enable controlling the behaviour of swarms of agents. It has been shown in the literature that the point of convergence and motion of a swarm of ...

Unmanned aerial vehicles (UAV) have the potential to be used for search and surveillance missions... more Unmanned aerial vehicles (UAV) have the potential to be used for search and surveillance missions, and as munitions in the battlefield. The UAVs are deployed in swarms as they may not have sufficient computational, sensor, and operational capability to complete the task single-handedly. A desirable feature for these UAV swarms is the capability of intelligent autonomous decision making and coordination, with minimal or no centralized control. In this chapter, we present decentralized and distributed task allocation schemes based on concepts from team theory, game theory, and from negotiation techniques used in decision-making problems arising in economics, and apply these to design intelligent decision-making strategies for multiple UAV systems performing a wide area search and surveillance mission. We also address the task of searching an unknown environment, which is a major component in such missions, separately using game theoretical concepts.

210 IEEE INDIA ANNUAL CONFERENCE 20O4, INDICON 2004 Some Generalizations of Linear Cyclic Pursuit... more 210 IEEE INDIA ANNUAL CONFERENCE 20O4, INDICON 2004 Some Generalizations of Linear Cyclic Pursuit Arpita Sinha and Debasish Ghose Abstract—In this paper, the behaviour of a group of au-tonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple ...

IEEE Transactions on Automatic Control, 2006

Abstract—Cyclic pursuit is a simple distributed control law in which agent pursues agent + 1 modu... more Abstract—Cyclic pursuit is a simple distributed control law in which agent pursues agent + 1 modulo . We generalize existing results and show that by selecting the gains of the agents, the point of convergence of these agents can be controlled. The condition for convergence, ...

In this paper, the behaviour of a group of autonomous mobile agents under cyclic pursuit is studi... more In this paper, the behaviour of a group of autonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i + 1 modulo n. The equations of motion are linear, with no kinematic constraints on motion. Behaviourally, the agents are identical, but may have different controller gains.

A multiple UAV search and attack mission in a battlefield involves allocating UAVs to different t... more A multiple UAV search and attack mission in a battlefield involves allocating UAVs to different target tasks efficiently. This task allocation becomes difficult when there is no communication among the UAVs and the UAVs sensors have limited range to detect the targets and neighbouring UAVs, and assess target status. In this paper, we propose a team theoretic approach to efficiently allocate UAVs to the targets with the constraint that UAVs do not communicate among themselves and have limited sensor range. We study the performance of team theoretic approach for task allocation on a battle field scenario. The performance obtained through team theory is compared with two other methods, namely, limited sensor range but with communication among all the UAVs, and greedy strategy with limited sensor range and no communication. It is found that the team theoretic strategy performs the best even though it assumes limited sensor range and no communication.

Journal of Dynamic Systems Measurement and Control-transactions of The Asme, 2007

ABSTRACT In this paper behavior of a group of autonomous mobile agents under cyclic pursuit is st... more ABSTRACT In this paper behavior of a group of autonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i +1 mod n. The equations of motion are linear with no kinematic constraints on motion. Behaviorally, they are identical but may have different controller gains. We generalize existing results in the literature, which consider only homogenous gains, to the case where controller gains are heterogenous. We show that, by selecting suitable controller gains, collective behavior of agents can be controlled significantly to obtain not only point convergence but also directed motion. In particular we obtain analytical results that relate the controller gains to the direction of movement of the agents when the system is unstable. Invariance results with respect to the pursuit sequence are also proved. Finally, we also obtain some results that show some aspects of system behavior that is invariant with respect to finite switching of connections. Simulation experiments are given in support of the analytical results.

European Journal of Control, 2009

Abstract One of the major tasks in swarm intelligence is to design decentralized but homogenoeus ... more Abstract One of the major tasks in swarm intelligence is to design decentralized but homogenoeus strategies to enable controlling the behaviour of swarms of agents. It has been shown in the literature that the point of convergence and motion of a swarm of ...

Unmanned aerial vehicles (UAV) have the potential to be used for search and surveillance missions... more Unmanned aerial vehicles (UAV) have the potential to be used for search and surveillance missions, and as munitions in the battlefield. The UAVs are deployed in swarms as they may not have sufficient computational, sensor, and operational capability to complete the task single-handedly. A desirable feature for these UAV swarms is the capability of intelligent autonomous decision making and coordination, with minimal or no centralized control. In this chapter, we present decentralized and distributed task allocation schemes based on concepts from team theory, game theory, and from negotiation techniques used in decision-making problems arising in economics, and apply these to design intelligent decision-making strategies for multiple UAV systems performing a wide area search and surveillance mission. We also address the task of searching an unknown environment, which is a major component in such missions, separately using game theoretical concepts.

210 IEEE INDIA ANNUAL CONFERENCE 20O4, INDICON 2004 Some Generalizations of Linear Cyclic Pursuit... more 210 IEEE INDIA ANNUAL CONFERENCE 20O4, INDICON 2004 Some Generalizations of Linear Cyclic Pursuit Arpita Sinha and Debasish Ghose Abstract—In this paper, the behaviour of a group of au-tonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple ...

IEEE Transactions on Automatic Control, 2006

Abstract—Cyclic pursuit is a simple distributed control law in which agent pursues agent + 1 modu... more Abstract—Cyclic pursuit is a simple distributed control law in which agent pursues agent + 1 modulo . We generalize existing results and show that by selecting the gains of the agents, the point of convergence of these agents can be controlled. The condition for convergence, ...

In this paper, the behaviour of a group of autonomous mobile agents under cyclic pursuit is studi... more In this paper, the behaviour of a group of autonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i + 1 modulo n. The equations of motion are linear, with no kinematic constraints on motion. Behaviourally, the agents are identical, but may have different controller gains.

A multiple UAV search and attack mission in a battlefield involves allocating UAVs to different t... more A multiple UAV search and attack mission in a battlefield involves allocating UAVs to different target tasks efficiently. This task allocation becomes difficult when there is no communication among the UAVs and the UAVs sensors have limited range to detect the targets and neighbouring UAVs, and assess target status. In this paper, we propose a team theoretic approach to efficiently allocate UAVs to the targets with the constraint that UAVs do not communicate among themselves and have limited sensor range. We study the performance of team theoretic approach for task allocation on a battle field scenario. The performance obtained through team theory is compared with two other methods, namely, limited sensor range but with communication among all the UAVs, and greedy strategy with limited sensor range and no communication. It is found that the team theoretic strategy performs the best even though it assumes limited sensor range and no communication.

Journal of Dynamic Systems Measurement and Control-transactions of The Asme, 2007

ABSTRACT In this paper behavior of a group of autonomous mobile agents under cyclic pursuit is st... more ABSTRACT In this paper behavior of a group of autonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i +1 mod n. The equations of motion are linear with no kinematic constraints on motion. Behaviorally, they are identical but may have different controller gains. We generalize existing results in the literature, which consider only homogenous gains, to the case where controller gains are heterogenous. We show that, by selecting suitable controller gains, collective behavior of agents can be controlled significantly to obtain not only point convergence but also directed motion. In particular we obtain analytical results that relate the controller gains to the direction of movement of the agents when the system is unstable. Invariance results with respect to the pursuit sequence are also proved. Finally, we also obtain some results that show some aspects of system behavior that is invariant with respect to finite switching of connections. Simulation experiments are given in support of the analytical results.