Decentralized navigation method for a robotic swarm with nonhomogeneous abilities

Yoshimoto, Masahiro; Endo, Takahiro; Maeda, Ryuma; Matsuno, Fumitoshi

doi:10.1007/s10514-018-9774-x

Cited by 15 publications

(18 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, it is an interesting problem to consider the formation control for heterogeneous robotic swarms with crossing motion. Here, heterogeneous robotic swarms mean that each agent has different abilities, including translational velocity, sensing distance, etc., as in our previous study [36,37]. In addition, we did not consider the extension of the proposed controller to the case in which the underlying systems are in an uncertain or time-varying networked environment [38].…”

Section: Discussionmentioning

confidence: 99%

Distributed formation for robotic swarms considering their crossing motion

Kobayashi

Endo

Matsuno

2018

Journal of the Franklin Institute

Self Cite

View full text Add to dashboard Cite

This paper discusses formation problem for robotic swarms when multiple robotic swarms cross one another's path. To realize the crossing motion, collision avoidance between agents is an important issue, with the potential to cause a general mix-up of formation during the crossing motion. To realize an orderly and well-organized crossing motion with the least mix-up, as well as collision avoidance, we propose a distributed controller. This well-organized crossing motion can realize visually appealing and highly entertaining robotic mass games. This paper proposes a distributed controller using the gradient of the cost functions about the formation maintenance, collision avoidance, and tracking to the desired trajectory. We then prove that we can achieve a well-organized crossing motion of multiple robotic swarms under several assumptions. Finally, experimental and numerical simulations are carried out to investigate whether the well-organized crossing motion can be achieved.

show abstract

Section: Discussionmentioning

confidence: 99%

Distributed formation for robotic swarms considering their crossing motion

Kobayashi

Endo

Matsuno

2018

Journal of the Franklin Institute

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consensus algorithm for distributed sensors through data fusion of neighboring nodes that outperformed classic algorithms by 16.5% with little to no delay [12]. Finally, a leader-follower method for swarm navigation using only local data has been tested with physical drones [13].…”

Section: B Related Workmentioning

confidence: 99%

“…A novel particle swarm optimization framework for decentralized consensus --+ --- [13] A method for swarm navigation using only local data -…”

Section: B Related Workmentioning

confidence: 99%

“…Regardless of location, a significant issue in autonomous swarms is decentralized coordination and control. Approaches to this problem include probabilistic density control of autonomous swarms [10], controllers for shape generation [11], sensor consensus achievement through particle swarm optimization [12], and non-homogeneous robotic swarm navigation [13]. Probabilistic density control of autonomous swarms has been achieved using Markov chain based approach using a decentralized density computation [10].…”

Section: B Related Workmentioning

confidence: 99%

“…Control over a drone swarm and location awareness through motion capture -+ --+ + [9] Review of swarm localization and positioning in closed environments -+ -+ + - [10] Markov chain based approach for the probabilistic density control of a swarm -+ + --- [11] Decentralized controller methods for swarm shape generation -+ + + -- [12] A novel particle swarm optimization framework for decentralized consensus --+ --- [13] A method for swarm navigation using only local data -+ + + -+ [14] Decentralized clustering and dispersion algorithms for autonomous swarms + + + --- [15] Survey on UAV swarms with inspiration from bird flocks -+ + --- [16] Optimization data collection technique for drone swarms and sensor networks…”

Section: B Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Adversarial Impacts on Autonomous Decentralized Lightweight Swarms

Wolf

Cooley

Borowczak

2019

2019 IEEE International Smart Cities Conference (ISC2)

View full text Add to dashboard Cite

The decreased size and cost of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has enabled the use of swarms of unmanned autonomous vehicles to accomplish a variety of tasks. By utilizing swarming behaviors, it is possible to efficiently accomplish coordinated tasks while minimizing per-drone computational requirements. Some drones rely on decentralized protocols that exhibit emergent behavior across the swarm. While fully decentralized algorithms remove obvious attack vectors their susceptibility to external influence is less understood. This work investigates the influences that can compromise the functionality of an autonomous swarm leading to hazardous situations and cascading vulnerabilities. When a swarm is tasked with missions involving the safety or health of humans, external influences could have serious consequences. The adversarial swarm in this work utilizes an attack vector embedded within the decentralized movement algorithm of a previously defined autonomous swarm designed to create a perimeter sentry swarm. Various simulations confirm the adversarial swarm's ability to capture significant portions (6-23%) of the perimeter.

show abstract

Decentralized Navigation in 3D Space of a Robotic Swarm with Heterogeneous Abilities

Tanaka

Endo

Matsuno

2022

Distributed Autonomous Robotic Systems

Self Cite

View full text Add to dashboard Cite

This paper proposes a decentralized method for navigation of multiple robots, each of which has different abilities, by a single leader robot in 3D space, especially focusing on the connectivity maintenance. We assume a swarm of robots whose sensing ranges, maximum speeds and maximum accelerations are different. For such robots, we propose a control method for maintaining the whole connectivity by each agent's keeping local connectivity in a decentralized way. We also mathematically prove that the proposed method can enable multiple robots to navigate in 3D space while keeping the connectivity. Finally, numerical simulation results are presented to confirm the effectiveness of the proposed method.

show abstract

Decentralized navigation method for a robotic swarm with nonhomogeneous abilities

Cited by 15 publications

References 28 publications

Distributed formation for robotic swarms considering their crossing motion

Distributed formation for robotic swarms considering their crossing motion

Adversarial Impacts on Autonomous Decentralized Lightweight Swarms

Decentralized Navigation in 3D Space of a Robotic Swarm with Heterogeneous Abilities

Contact Info

Product

Resources

About