Department of Computer Science and Information Systems

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Author: search.filters.author.Mohan, SudeeptSubject: search.filters.subject.Multi-robot systems

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    D-MRFTE: A Decentralized Relay-Based Approach for Multi-Robot Unknown Area Exploration
    (IEEE, 2023) Gautam, Avinash; Mohan, Sudeept; Shekhawat, Virendra Singh
    In this paper, a decentralized relay-based approach (D-MRFTE) for unknown area exploration using a team of autonomous mobile robots is proposed under communication constraints. Using the relay robots, the multi-robot system forms a high-latency decentralized network with distributed copies of exploration information for which eventual consistency and completeness are ensured through meetups. The meetups act as a safety net and set a bound on latency by ensuring data transfer at periodic intervals whenever the multi-robot network gets fragmented. The information exchange related to the robot’s state and the ongoing exploration is facilitated by the relay robots. The robots use timestamps to assimilate the latest available information by using version vectors. To achieve a consistent state of explorer robots, the relays schedule meetups with other relays they come in contact with, creating a tightly-knit group. Our approach, under two communication models, i.e., Disk-based and Line-of-Sight-based, exhibits superior performance compared with two state-of-the-art algorithms in terms of completion time and distance traveled by the robot team. The simulations are conducted in a Player/Stage simulator with different robot team sizes.
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    A distributed algorithm for circle formation by multiple mobile robots
    (IEEE, 2013) Gautam, Avinash; Mohan, Sudeept
    This paper suggests a distributed, decentralized approach for positioning multiple mobile robots in a circular formation in a semi synchronous setting. The problem of the circle formation with multiple robots which are arbitrarily placed on a 2D plane requires all robots to be uniformly positioned (i.e., at an equal angular distance of 2ŏ/N, where N = number of robots) on the circle circumference. The suggested approach uses explicit inter robot communication by way of message passing and forms a token ring based network. It uses the distributed solution of one of the classical synchronization problem often used in distributed systems, the Dining Philosopher Problem, for the robots to synchronize during their activation cycles.
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    Positioning multiple mobile robots for geometric pattern formation: An empirical analysis
    (IEEE, 2014) Mohan, Sudeept; Gautam, Avinash
    This paper presents an experimental setup for absolute positioning of multiple mobile robots in an indoor environment using a low cost camera. Localization or positioning of mobile robot in its environment is crucial for deciding its future course of action. In this paper we have proposed to use an overhead camera for positioning multiple mobile robots which are required to act as a team. Also we have tested the efficacy of two existing distributed algorithms for circle formation using a team of five e-puck robots. The first algorithm is mathematically proven with many assumptions about the sensing and motion capabilities of mobile robots which are not feasible in the real world. In the second algorithm the authors have considered explicit inter robot communication and have utilized the distributed solution of a well known algorithm often discussed in distributed computing - the Dinning Philosophers Problem for the robots to synchronize during their activation cycle. The contribution of this paper is twofold i.e., first, a practical low cost, multi-robot positioning system is proposed and second, experimental evaluation of two distributed algorithms for circle formation by a team of mobile robots have been carried out. It is seen that the second algorithm outperforms the first.
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    A distributed algorithm for balanced multi-robot task allocation
    (IEEE, 2016) Gautam, Avinash; Mohan, Sudeept
    In this paper the problem of static multi-robot task allocation is addressed. It is concerned with the distribution of static tasks in an environment to robots such that the robots complete the tasks in an optimal fashion. The cost of completing a task is proportional to the distance travelled by a robot to visit that task. This problem is of particular importance in multi-robot systems because finding an optimal solution is NP-hard. Earlier work has paid less attention towards load balanced task allocation. In this paper, a completely distributed algorithm is proposed. A travelling salesman tour (TST) considering all task locations is computed using distributed genetic algorithm. The TST is partitioned into fragments that are distributed amongst the robots using a novel auction algorithm. The proposed algorithm is compared with a state of the art algorithm in simulation. The results thus obtained substantiate the fact that the proposed algorithm shows improved performance in terms of load balanced distribution of tasks to the individual robots in multi-robot system.
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    FAST: Synchronous Frontier Allocation for Scalable Online Multi-Robot Terrain Coverage
    (Springer, 2017-09) Gautam, Avinash; Mohan, Sudeept
    We propose Frontier Allocation Synchronized by Token passing (FAST), a distributed algorithm for online terrain coverage using multiple mobile robots, ensuring mutually exclusive selection of frontier cells. Many existing approaches cover the terrain in an irregular fashion, without considering the usability of the already covered region. For instance, in the task of floor cleaning in an office building, these approaches do not guarantee the cleanliness of large unbroken areas until a majority of the task is complete. FAST on the other hand, incrementally traverses the terrain generating structured trajectories for each robot. Following a structured trajectory for coverage path planning is proven to be a very powerful approach in literature. This renders large portions of the terrain usable even before the completion of the coverage task. The novel map representation techniques used in FAST render it scalable to large terrains, without affecting the volume of communication among robots. Moreover, the distributed nature of FAST allows incorporation of fault-tolerance mechanisms.
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    Balanced partitioning of workspace for efficient multi-robot coordination
    (IEEE, 2017) Shekhawat, Virendra Singh; Gautam, Avinash; Mohan, Sudeept
    Multi-robot terrain coverage approaches that are based on Voronoi partitioning produce unbalanced partitions of the workspace resulting in uneven distribution of the workload to the individual robots. The proposed approach creates partitions of the workspace such that the regions to be covered by individual robots are maximally balanced. This type of partitioning can be especially useful in tasks like floor cleaning, surveillance etc. The proposed approach is suitable for use in indoor environments like office buildings, hospitals etc. It is assumed that the grid map of the workspace is already known. The workspace is transformed into a topological weighted connected graph. Vertex weight is defined by the size of the area it represents. This graph is then partitioned into sub-graphs that are maximally balanced in terms of vertex weights using genetic algorithm. These sub-graphs thus obtained represent balanced partitions which are assigned to the individual robots for further processing.
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    Experimental Evaluation of Multi-Robot Online Terrain Coverage Approach
    (IEEE, 2018) Shekhawat, Virendra Singh; Gautam, Avinash; Mohan, Sudeept
    This paper presents a empirical evaluation of some approaches suggested in the literature for solving the online terrain coverage task. Our first contribution is that, we have implemented in simulation four state-of-the-art approaches. The first two approaches are based on structured trajectories and use backtracking mechanism for task allocation. The other two are based on the behavior of ants. Also, we have modified one of the state-of-the-art approaches and improved its performance in terms of computation time. The second contribution is that, we have developed a practical test-bed comprising of multiple differential drive robots that are able to coordinate with each other in a distributed fashion by wirelessly communicating with their team-mates. We have implemented the representative set of approaches on our test-bed. The same test-bed can be leveraged for validating multi-robot coordination approaches for solving other tasks like patrolling, foraging, etc.
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    A Graph Partitioning Approach for Fast Exploration with Multi-Robot Coordination
    (IEEE, 2019) Shekhawat, Virendra Singh; Mohan, Sudeept; Gautam, Avinash
    A multi-robot exploration approach is suggested in this paper that works on the premise that the topo-metric map of the indoor environment is known a priori. Genetic Algorithms (GAs) are used for spatial partitioning of the topo-metric graph of the environment. Each spatial partition, which represents the sub-graph, is apportioned to a unique robot by using the Hungarian method for task assignment in conjunction with Bully Algorithm for leader election. In the case of robot(s) failure, graph re-partitioning and single item auctions are used for re-assigning the remaining task(s) of the failed robot(s) to other robots. The proposed approach performs better than a recent state-of-the-art strategy that employs Delaunay triangulation and multi-prim algorithm for multi-robot exploration. Empirical results obtained in simulation by varying the number of robots in two different and complex environments prove the efficacy of the proposed approach.
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    A review of research in multi-robot systems
    (IEEE, 2012) Gautam, Avinash; Mohan, Sudeept
    Formally, a collection of two or more autonomous mobile robots working together are termed as teams or societies of mobile robots. In multi robot systems simple robots are allowed to coordinate with each other to achieve some well defined goals. In these kinds of systems robots are far less capable as an entity, but the real power lies in cooperation of multiple robots. The simplicity of multi-robots have produced a potentially wide set of applications such as military missions (battlefield surveillance), searching for survivors in disaster hit areas, parallel and simultaneous transportation of vehicles, and delivery of payloads. Although the research on multi-robot systems has attracted considerable attention worldwide in the past decade, the research in this area is still in its infancy. This paper surveys various interaction techniques in multi robot systems which are important with respect to goal attainment and task completion.
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    Cluster, Allocate, Cover: An Efficient Approach for Multi-robot Coverage
    (IEEE, 2015) Mohan, Sudeept; Gautam, Avinash
    This article presents an algorithm for online multirobot coverage that proceeds with minimal knowledge of the already explored region and the frontier cells. It creates clusters of frontier cells which are designated to robots using an optimal assignment scheme. Coverage is then performed using a novel path planning technique. Many approaches that use clustering for multi-robot coverage do not specify strict time criteria for re-clustering. Moreover, the motion plans they use result in redundant coverage. To overcome these limitations, an appropriate motion plan for the robots is chosen based on the context of already covered frontiers. Dispersion of robots is vital for efficient coverage and is an emergent behavior in our approach. The efficacy of the proposed approach is tested in simulation and on a multi-robot test-bed. The algorithm performs better than some state of the art approaches.