arXiv subjects

Debasish Ghose

Publications and source records attributed to Debasish Ghose.

45 records · Page 3Linked to original sources

arXiv2018

Influence Dynamics and Consensus in an Opinion-Neighborhood based Modified Vicsek-like Social Network

We propose a modified Vicsek-like model to study influence dynamics and opinion formation in social networks. We work on the premise that opinions of members of a group may be considered to be analogous to the direction of motion of a particle in space. The opinions are susceptible to change under the influence of familiar individuals who maintain similar beliefs. This is unlike the bounded-confidence models which solely rely on interactions based on closeness of opinions. The influence network evolves either when similar-minded individuals acquaint or when they fall out over their beliefs. This yields an adaptive network to which are assigned dynamic centrality scores and varying influence strengths. A mix of individuals - rigid and flexible - is assumed to constitute groups - liberal and conservative. We analyse emergent group behaviours subject to different initial conditions, agent types, their densities and tolerances. The model accurately predicts the role of rigid agents in hampering consensus. Also, a few structural properties of the dynamic network, which result as a consequence of the proposed model have been established.

cs.SI↗

arXiv2017

Asymptotic Optimality of Rapidly Exploring Random Tree

In this paper we investigate the asymptotic optimality property of a randomized sampling based motion planner, namely RRT. We prove that a RRT planner is not an asymptotically optimal motion planner. Our result, while being consistent with similar results which exist in the literature, however, brings out an important characteristics of a RRT planner. We show that the degree distribution of the tree vertices follows a power law in an asymptotic sense. A simulation result is presented to support the theoretical claim. Based on these results we also try to establish a simple necessary condition for sampling based motion planners to be asymptotically optimal.

cs.RO↗

arXiv2016

Phase Balancing of Two and Three-Agent Heterogeneous Gain Systems With Extensions to Multiple Agents

This paper studies the phase balancing of a two and three-agent system where the agents are coupled through heterogeneous controller gains. Balancing refers to the situation in which the movement of agents causes the position of their centroid to become stationary. We generalize existing results and show that by using heterogeneous controller gains, the velocity directions of the agents in balanced formation can be controlled. The effect of heterogeneous gains on the reachable set of these velocity directions is further analyzed. For the two-agents case, the locus of steady-state location of the centroid is also analyzed against the variations in the heterogeneous controller gains. Simulations are given to illustrate the theoretical findings.

eess.SY↗

arXiv2016

Collective Circular Motion of Multi-Agent Systems in Synchronized and Balanced Formations With Second-Order Rotational Dynamics

This paper considers the collective circular motion of multi-agent systems in which all the agents are required to traverse different circles or a common circle at a prescribed angular velocity. It is required to achieve these collective motions with the heading angles of the agents synchronized or balanced. In synchronization, the agents and their centroid have a common velocity direction, while in balancing, the movement of agents causes the location of the centroid to become stationary. The agents considered are initially moving at unit speed around individual circles at different angular velocities. It is assumed that the agents are subjected to limited communication constraints, and exchange relative information according to a time-invariant undirected graph. We present suitable feedback control laws for each of these motion coordination tasks by considering a second-order rotational dynamics of the agent. Simulations are given to illustrate the theoretical findings.

eess.SY↗

arXiv2016

Synchronization of Multi-Agent Systems With Heterogeneous Controllers

This paper studies the synchronization of a multi-agent system where the agents are coupled through heterogeneous controller gains. Synchronization refers to the situation where all the agents in a group have a common velocity direction. We generalize existing results and show that by using heterogeneous controller gains, the final velocity direction at which the system of agents synchronize can be controlled. The effect of heterogeneous gains on the reachable set of this final velocity direction is further analyzed. We also show that for realistic systems, a limited control force to stabilize the agents to the synchronized condition can be achieved by confining these heterogeneous controller gains to an upper bound. Simulations are given to support the theoretical findings.

eess.SY↗

arXiv2011

Coverage Optimization using Generalized Voronoi Partition

In this paper a generalization of the Voronoi partition is used for optimal deployment of autonomous agents carrying sensors with heterogeneous capabilities, to maximize the sensor coverage. The generalized centroidal Voronoi configuration, in which the agents are located at the centroids of the corresponding generalized Voronoi cells, is shown to be a local optimal configuration. Simulation results are presented to illustrate the presented deployment strategy.

math.OC↗

arXiv2011

On Consensus under Polynomial Protocols

In this paper we explore the possibility of using computational algebraic methods to analyze a class of consensus protocols. We state some necessary conditions for convergence under consensus protocols that are polynomials.

cs.SC↗

arXiv2009

Generalized Voronoi Partition Based Multi-Agent Search using Heterogeneous Sensors

In this paper we propose search strategies for heterogeneous multi-agent systems. Multiple agents, equipped with communication gadget, computational capability, and sensors having heterogeneous capabilities, are deployed in the search space to gather information such as presence of targets. Lack of information about the search space is modeled as an uncertainty density distribution. The uncertainty is reduced on collection of information by the search agents. We propose a generalization of Voronoi partition incorporating the heterogeneity in sensor capabilities, and design optimal deployment strategies for multiple agents, maximizing a single step search effectiveness. The optimal deployment forms the basis for two search strategies, namely, {\em heterogeneous sequential deploy and search} and {\em heterogeneous combined deploy and search}. We prove that the proposed strategies can reduce the uncertainty density to arbitrarily low level under ideal conditions. We provide a few formal analysis results related to stability and convergence of the proposed control laws, and to spatial distributedness of the strategies under constraints such as limit on maximum speed of agents, agents moving with constant speed and limit on sensor range. Simulation results are provided to validate the theoretical results presented in the paper.

math.OC↗

arXiv2009

Performance of a Class of Multi-Robot Deploy and Search Strategies based on Centroidal Voronoi Configurations

This paper considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is a system of autonomous mobile robots equipped with required sensors and communication equipment deployed in a search space to gather information. The lack of information about the search space is modeled as an uncertainty density distribution over the search space. A {\em combined deploy and search} (CDS) strategy has been formulated as a modification to {\em sequential deploy and search} (SDS) strategy presented in our previous work. The optimal deployment strategy using Voronoi partition forms the basis for these two search strategies. The strategies are analyzed in presence of constraints on robot speed and limit on sensor range for convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the strategies on parameters such as number of robots, speed of robots, and their sensor range limits.

math.OC↗