Herding by caging: a formation-based motion planning framework for guiding mobile agents

Song, Haoran; Varava, Anastasiia; Kravchenko, Oleksandr; Kragić, Danica; Wang, Michael Yu; Pokorny, Florian T.; Hang, Kaiyu

doi:10.1007/s10514-021-09975-8

Cited by 21 publications

(13 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Extending this work, Pierson and Schwager [6] have presented a 3-D herding algorithm based on the dimension reduction of the whole multi-agent system. Similar works can be found in [10] and [11], where caging-based algorithms for guiding a flock of agents are proposed. El-Fiqi et al [8] have presented a centralized shepherding algorithm that assigns a path to each steering agent.…”

Section: Introductionmentioning

confidence: 78%

Communication-Free Shepherding Navigation with Multiple Steering Agents

Li¹,

Ogura²,

Wakamiya³

2022

Preprint

View full text Add to dashboard Cite

Swarm guidance addresses a challenging problem considering the navigation and control of a group of passive agents. To solve this problem, shepherding offers a bio-inspired technique of navigating such group of agents by using external steering agents with appropriately designed movement law. Although most shepherding researches are mainly based on the availability of centralized instructions, these assumptions are not realistic enough to solve some emerging application problems. Therefore, this paper presents a decentralized shepherding method where each steering agent makes movements based on its own observation without any inter-agent communication. Our numerical simulations confirm the effectiveness of the proposed method by showing its high success rate and low costs in various placement patterns. These advantages particularly improve with the increase in the number of steering agents.

show abstract

Section: Introductionmentioning

confidence: 78%

Communication-Free Shepherding Navigation with Multiple Steering Agents

Li¹,

Ogura²,

Wakamiya³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Montijano et al (2013) proposed a herding strategy based on elliptical orbits to entrap a passive agent whose position is uncertain. Varava et al (2017); Song et al (2021) developed a "herding by caging" solution, based on geometric considerations and motion planning techniques to arrange the herder agents around the flock. A similar formation was presented in Chipade and Panagou (2019), and further developed in Chipade et al (2021), to let herders identify clusters of flocking adversarial agents, dynamically encircle and drive them to a safe zone.…”

Section: Related Workmentioning

confidence: 99%

“…A herder's action is based on the global knowledge of the environment and of the positions of all other agents. With respect to other solutions in the literature (Lien et al 2004;Pierson and Schwager 2018;Chipade et al 2021;Song et al 2021), our approach does not involve the use of ad hoc formation control strategies to force the herders surround the herd, but we rather enforce cooperation between herders by dynamically dividing the plane among them by means of simple yet effective and robust rules that can be easily implemented in real robots.…”

Section: Contributions Of This Papermentioning

confidence: 99%

“…Notable herding solutions are those proposed in Vaughan et al (2000), Lien et al (2004), Strombom et al (2014), Paranjape et al (2018), Licitra et al (2019) for single herders and in Lien et al (2005), Haque et al (2009), Lee and Kim (2017), Pierson and Schwager (2018), Nalepka et al (2017b), Montijano et al (2013), Varava et al (2017), Song et al (2021), Chipade and Panagou (2019), Sebastián and Montijano (2021) for multiple herders.…”

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Herding stochastic autonomous agents via local control rules and online target selection strategies

et al. 2022

View full text Add to dashboard Cite

We propose a simple yet effective set of local control rules to make a small group of “herder agents” collect and contain in a desired region a large ensemble of non-cooperative, non-flocking stochastic “target agents” in the plane. We investigate the robustness of the proposed strategies to variations of the number of target agents and the strength of the repulsive force they feel when in proximity of the herders. The effectiveness of the proposed approach is confirmed in both simulations in ROS and experiments on real robots.

show abstract

“…Many herding solutions are restricted to a single evader [6,10,21], deal with the evaders one by one [8], assume cooperation [19,21], or only deal with a similar number of herders and evaders [15,17]. Inspired by surveillance and caging-like solutions [1,18], and to overcome the limitation on the number of controlled variables, we propose a novel dynamic assignment strategy to decide online the best evaders to directly control. The rest of the herd is indirectly controlled, but all the evaders converge to the desired tracking reference while ensuring that none of them escape.…”

Section: Introductionmentioning

confidence: 99%

Multi-robot Implicit Control of Herds

Sebastián

Montijano

2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

This paper solves the problem of herding countless evaders by means of a few robots. The objective is to steer all the evaders towards a desired tracking reference while avoiding escapes. The problem is very challenging due to the highly complex repulsive evaders' dynamics and the underdetermined states to control. We propose a solution that is based on Implicit Control and a novel dynamic assignment strategy to select the evaders to be directly controlled. The former is a general technique that explicitly computes control inputs even in highly complex input-nonaffine dynamics. The latter is built upon a convex-hull dynamic clustering inspired by the Voronoi tessellation problem. The combination of both allows to choose the best evaders to directly control, while the others are indirectly controlled by exploiting the repulsive interactions among them. Simulations show that massive herds can be herd throughout complex patterns by means of a few herders.

show abstract

Herding by caging: a formation-based motion planning framework for guiding mobile agents

Cited by 21 publications

References 27 publications

Communication-Free Shepherding Navigation with Multiple Steering Agents

Communication-Free Shepherding Navigation with Multiple Steering Agents

Herding stochastic autonomous agents via local control rules and online target selection strategies

Multi-robot Implicit Control of Herds

Contact Info

Product

Resources

About