Adaptive Multi-Agent Coverage Control With Obstacle Avoidance

Bai, Yuchuan; Wang, Yujie; Magid, Evgeni; Sun, Rong

doi:10.1109/lcsys.2021.3087609

Cited by 18 publications

(8 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The FAT is an effective tool to deal with control systems with time-varying nonlinear uncertainties [23]. For instance, if d(t) is an unknown time-varying function in a control system, one can utilize weighted basis functions to represent d(t), at each time instant, as [10], [23]- [28]…”

Section: B Fatmentioning

confidence: 99%

“…4(d)) is conducted. The nominal controller is selected as the non-switched controller designed in [10]. The blue polygons in Fig.…”

Section: Proof Define Hi Asmentioning

confidence: 99%

“…Different from our previous work [10], in this paper, we present a solution to the collision avoidance problem in the coverage control based on the CBF [11], which does not require a redesign of the Voronoi tessellation. Instead, safety range for each agent is constructed such that the collision avoidance between agents can be guaranteed.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Multi-Agent Control with Dynamic Obstacle Avoidance in a Limited Region

Bai

Wang

Xiong

et al. 2022

2022 American Control Conference (ACC)

Self Cite

View full text Add to dashboard Cite

This paper presents a safe adaptive coverage controller for multi-agent systems with actuator faults and timevarying uncertainties. The centroidal Voronoi tessellation (CVT) is applied to generate an optimal configuration of multi-agent systems for covering an area of interest. As conventional CVT based controller cannot prevent collisions between agents with non-zero size, a control barrier function (CBF) based controller is developed to ensure collision avoidance with a function approximation technique (FAT) based design to deal with system uncertainties. The proposed controller is verified under simulations.

show abstract

Section: B Fatmentioning

confidence: 99%

“…4(d)) is conducted. The nominal controller is selected as the non-switched controller designed in [10]. The blue polygons in Fig.…”

Section: Proof Define Hi Asmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Multi-Agent Control with Dynamic Obstacle Avoidance in a Limited Region

Bai

Wang

Xiong

et al. 2022

2022 American Control Conference (ACC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Waydo [28,29] proposed vehicle motion planning using the steam function only on two dimensional plane; its biggest advantage is to avoid the cumbersome online optimization in each time slot based on MPC algorithm when a vehicle is avoiding a round obstacle. However, they also do not consider the problem of multi-agent with fixed formation avoiding obstacles [30]. In addition, the discrete multi-agent system combing various MPC algorithms could calculated out the predicted trajectory of obstacle avoidance.…”

Section: Introductionmentioning

confidence: 99%

“…It needs more sophisticated technique to construct efficient penalty functions and constraint conditions in various improved MPC methods [16,[22][23][24]26] for realizing obstacle avoidance, and spends a huge amount of computation for online rolling optimization. The amount of calculation is relatively reduced by using APF method to design obstacle avoidance algorithms for multi-agent, but including its various improved APF methods [15][16][17][18][19][20][21] cannot completely avoid the local minimum problem; It is efficient to avoid the local minimum problem by using sink flow [28][29][30], however, the target position of multi-agent motion needs to be given in advance. According to our proposed methods, multi-UAV formation can avoid complex obstacle group and another moving multi-UAV formation on any path without specifying the navigation destination.…”

Section: Introductionmentioning

confidence: 99%

Research on the strategies for collision avoidance of multi‐UAV with three dimensional formation in combination of consensus algorithm and uniform flow

Cao

2023

IET Control Theory & Appl

View full text Add to dashboard Cite

The paper proposes the method of uniform flow loading the improved consensus algorithm to achieve obstacle avoidance for multi‐UAV with 3‐D formation. In view of that the flow function is generally only applicable to two dimensional flow field, dimension reduction is to treat multi‐UAV formation as each UAV flows around along the circular surface of the projected cylinder of spherical obstacle at its different heights. To formation guaranteeing the smooth realization of obstacle avoidance of multi‐UAV formation centered on the leader, it is used the tactics of virtually expanding the radius of these static or moving equivalent cylindrical obstacles to reserve a certain space. The innovation of this strategy is to further reduce the possibility of collision between UAV formation and the edge of obstacles, meanwhile the problem of multi‐UAV formation avoiding obstacles is transformed into the problem of collision avoidance navigation for the leader treated as a particle. It is considered collision avoidance for multi‐UAV formation under three scenarios assumed are the most common situations, and the simulation experimental results of these scenarios are demonstrated on the validity of the designed experiments based on these algorithms.

show abstract

Coverage control of unicycle multi‐agent network in dynamic environment

Sun

Liu

Chi

et al. 2021

Math Methods in App Sciences

View full text Add to dashboard Cite

This paper studies the coverage control problem of an unicycle multi‐agent network with external disturbance in a dynamic environment which is described by a time‐varying density function. It is a challenging task to design a coverage control to simultaneously handle the external disturbance, underactuated model and time‐varying density function. Based on Voronoi partition, we proposed a coverage control approach which can maximize the metric function via robust tracking the Voronoi centroid with external disturbance. It is worth to mentioning that the angle of motion of the unicycle agent can align with the Voronoi centroid in finite time. Finally, the effectiveness of the proposed control is shown by simulation results.

show abstract

Adaptive Multi-Agent Coverage Control With Obstacle Avoidance

Cited by 18 publications

References 23 publications

Adaptive Multi-Agent Control with Dynamic Obstacle Avoidance in a Limited Region

Adaptive Multi-Agent Control with Dynamic Obstacle Avoidance in a Limited Region

Research on the strategies for collision avoidance of multi‐UAV with three dimensional formation in combination of consensus algorithm and uniform flow

Coverage control of unicycle multi‐agent network in dynamic environment

Contact Info

Product

Resources

About