Segregation of Heterogeneous Units in a Swarm of Robotic Agents

Kumar, Manish; Garg, Devendra P.; Kumar, Vijay

doi:10.1109/tac.2010.2040494

Cited by 75 publications

(60 citation statements)

References 14 publications

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“…A desired property in this case is to keep robots close to their kins and avoid merging with other groups. This is called segregation and, as discussed previously [17], is a phenomenon that is seen in several biological systems. This paper presents a novel approach to swarm navigation that keeps large groups of robots segregated while safely navigating in a shared environment.…”

Section: Introductionmentioning

confidence: 89%

“…Moreover, many works have focused on its use together with flocking principles in order to obtain specific behaviors, such as area coverage [15], moving in formation [3], converging into shapes [8], shepherding [18], segregation [17], and so on. However, it is known that the method is not oscillation-free and suffers from local minima, which is an intrinsic property that can arise from the combination of potentials, specially in unknown environments.…”

Section: Related Workmentioning

confidence: 99%

“…In a recent work [17], a formal way of measuring segregation among groups of agents has been proposed. Two groups Γ A and Γ B are said to be segregated if the average distance between robots in the same group is less than the average distance between robots in distinct groups.…”

Section: Simulationsmentioning

confidence: 99%

See 2 more Smart Citations

On Segregative Behaviors Using Flocking and Velocity Obstacles

Santos

Campos

Chaimowicz

2014

Springer Tracts in Advanced Robotics

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This paper presents a novel approach to swarm navigation that combines hierarchical abstractions, flocking behaviors, and an efficient collision avoidance mechanism. Our main objective is to keep large groups of robots segregated while safely navigating in a shared environment. For this, we propose the Virtual Group Velocity Obstacle, which is an extension of the Velocity Obstacle concept for groups of robots. By augmenting velocity obstacles with flocking behaviors and hierarchical abstractions, we are able to navigate robotic swarms in a cohesive and smooth fashion. A series of simulations and real experiments were performed and the results show the effectiveness of the proposed approach.

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Section: Introductionmentioning

confidence: 89%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

On Segregative Behaviors Using Flocking and Velocity Obstacles

Santos

Campos

Chaimowicz

2014

Springer Tracts in Advanced Robotics

View full text Add to dashboard Cite

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“…Recent research on multi-MAV systems has focused on aspects of communication and maintenance of connectivity within the team members [2], [3], modeling of the swarm behavior by predicting individual behaviors [4], [5], task allocation and strategies for solving multiple tasks [6], [7], [8], and control and collision avoidance within the swarm [9], [10], [11], [12]. Topics covered in this paper are related mainly to control and stabilization of MAV teams.…”

Section: A Swarms Of Autonomous Vehiclesmentioning

confidence: 99%

System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization

et al. 2016

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Abstract-A complex system for control of swarms of Micro Aerial Vehicles (MAV), in literature also called as Unmanned Aerial Vehicles (UAV) or Unmanned Aerial Systems (UAS), stabilized via an onboard visual relative localization is described in this paper. The main purpose of this work is to verify the possibility of self-stabilization of multi-MAV groups without an external global positioning system. This approach enables the deployment of MAV swarms outside laboratory conditions, and it may be considered an enabling technique for utilizing fleets of MAVs in real-world scenarios. The proposed visualbased stabilization approach has been designed for numerous different multi-UAV robotic applications (leader-follower UAV formation stabilization, UAV swarm stabilization and deployment in surveillance scenarios, cooperative UAV sensory measurement) in this paper. Deployment of the system in real-world scenarios truthfully verifies its operational constraints, given by limited onboard sensing suites and processing capabilities. The performance of the presented approach (MAV control, motion planning, MAV stabilization, and trajectory planning) in multi-MAV applications has been validated by experimental results in indoor as well as in challenging outdoor environments (e.g., in windy conditions and in a former pit mine).

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“…Morgan et al [9] proposed a homotopy control scheme that realized the splitting and merging of flocking system with leader-following dynamics. Kumar et al [10] considered the splitting problem of heterogeneous swarm robots using different artificial potential functions. Chen et al [11] studied the aggregation and splitting problem of flocking system via a medium range repulsion force.…”

Section: Introductionmentioning

confidence: 99%