On Segregative Behaviors Using Flocking and Velocity Obstacles

Santos, Vinicius Graciano; Campos, Mário F. M.; Chaimowicz, Luiz

doi:10.1007/978-3-642-55146-8_9

Cited by 14 publications

(10 citation statements)

References 21 publications

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“…This is the implementation we will use throughout Section 4. Alternatively, Voronoi coverage can be used as inner loop for formation control of a group similar to [3,13] 5 and the entire group can be guided as single entity similar to [14,15] by RVO or ORCA in the outer control loop.…”

Section: Properties Of the Combined Methodsmentioning

confidence: 99%

On Combining Multi-robot Coverage and Reciprocal Collision Avoidance

Breitenmoser

Martinoli

2016

Springer Tracts in Advanced Robotics

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Although robotic coverage and collision avoidance are active areas of robotics research, the avoidance of collision situations between robots has often been neglected in the context of multi-robot coverage tasks. In fact, for robots of physical size, collisions are likely to happen during deployment and coverage in densely packed multi-robot configurations. For this reason, we aim to motivate by this paper the combined use of multi-robot coverage and reciprocal collision avoidance. We present a taxonomy of collision scenarios in multi-robot coverage problems. In particular, coverage tasks with built-in heterogeneity such as multiple antagonistic objectives or robot constraints are shown to benefit from the combination. Based on our taxonomy, we evaluate four representative robotic use cases in simulation by combining the specific methods of Voronoi coverage and reciprocal velocity obstacles.

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Section: Properties Of the Combined Methodsmentioning

confidence: 99%

On Combining Multi-robot Coverage and Reciprocal Collision Avoidance

Breitenmoser

Martinoli

2016

Springer Tracts in Advanced Robotics

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“…We use these methods in order to show how the chosen metric reflects the behavior of controllers that do not consider segregation. More detailed comparisons of these two with our proposed controllers can be found in [41] and [42].…”

Section: Methodsmentioning

confidence: 99%

Cohesion and segregation in swarm navigation

Santos

Chaimowicz

2014

Robotica

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The use of large groups of robots in the execution of complex tasks has received much attention in recent years. Generally called robotic swarms, these systems employ a large number of simple agents to perform different types of tasks. A basic requirement for most robotic swarms is the ability for safe navigation in shared environments. Particularly, two desired behaviors are to keep robots close to their kin and to avoid merging with distinct groups. These are respectively called cohesion and segregation, which are observed in several biological systems. In this paper, we investigate two different approaches that allow swarms of robots to navigate in a cohesive fashion while being segregated from other groups of agents.Our first approach is based on artificial potential fields and hierarchical abstractions. However, this method has one drawback: it needs a central entity which is able to communicate with all robots. To cope with this problem, we introduce a distributed mechanism that combines hierarchical abstractions, flocking behaviors, and an efficient collision avoidance mechanism.We perform simulated and real experiments in order to study the feasibility and effectiveness of our methods. Results show that both approaches ensure cohesion and segregation during swarm navigation.

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“…Concerning robotic swarms, Santos et al (2014) study the case where subgroups of a swarm meet during navigation, and each subgroup must remain segregated from the others while navigating. The navigation of different groups is also studied by Santos and Chaimowicz (2011), where a hierarchical approach is used in order to control each robotic group.…”

Section: Related Workmentioning

confidence: 99%

Avoiding target congestion on the navigation of robotic swarms

et al. 2016

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Robotic swarms are decentralized systems formed by a large number of robots. A common problem encountered in a swarm is congestion, as a great number of robots often must move towards the same region. This happens when robots have a common target, for example during foraging or waypoint navigation. We propose three algorithms to alleviate congestion: in the first, some robots stop moving towards the target for a random number of iterations; in the second, we divide the scenario in two regions: one for the robots that are moving towards the target, and another for the robots that are leaving the target; in the third, we combine the two previous algorithms. We evaluate our algorithms in simulation, where we show that all of them effectively improve navigation. Moreover, we perform an experimental analysis in the real world with ten robots, and show that all our approaches improve navigation with statistical significance.

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On Segregative Behaviors Using Flocking and Velocity Obstacles

Cited by 14 publications

References 21 publications

On Combining Multi-robot Coverage and Reciprocal Collision Avoidance

On Combining Multi-robot Coverage and Reciprocal Collision Avoidance

Cohesion and segregation in swarm navigation

Avoiding target congestion on the navigation of robotic swarms

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