Resilient Robust Connectivity for Multiagent Systems with Line of Sight Using Mixed-Integer Programming

Caregnato-Neto, Angelo; Máximo, Marcos R. O. A.; Afonso, Rubens Junqueira Magalhães

doi:10.1007/s40313-021-00809-7

Cited by 6 publications

(9 citation statements)

References 28 publications

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“…The robots and the connections between them are represented by the vertices and edges of the graph, respectively. The connectivity and robust connectivity of the graph G(k) imply the same properties for the communication network of the MAS at time step k [5].…”

Section: Connectivitymentioning

confidence: 88%

“…4, the purpose of the planning module is to provide commands to the trajectory tracking controllers of each agent. To this end, we employ the MPC-MIP formulation proposed in [5]. The following discrete-time state space prediction model is employed:…”

Section: Mpc-mip Motion Plannermentioning

confidence: 99%

“…The degree of the vertices representing the robots is encoded using constraint (14m). The 2-connectivity conditions that guarantee the robustness of the communication network are enforced by (14n) [5]. For details regarding this formulation, we refer the reader to the references associated with each element of the optimization problem.…”

Section: Mpc-mip Motion Plannermentioning

confidence: 99%

“…They must effectively collaborate towards the same global goal, as well as avoid collisions not only with potential obstacles in the environment but also between themselves. Their operation also frequently relies on the maintenance of the communication between the group elements [4], which is typically addressed as a connectivity problem in the graph-theoretical sense [5].…”

Section: Introductionmentioning

confidence: 99%

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Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming

Caregnato-Neto¹,

Máximo²,

Afonso³

2022

Preprint

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This work is concerned with the problem of planning trajectories and assigning tasks for a Multi-Agent System (MAS) comprised of differential drive robots. We propose a multirate hierarchical control structure that employs a planner based on robust Model Predictive Control (MPC) with mixed-integer programming (MIP) encoding. The planner computes trajectories and assigns tasks for each element of the group in real-time, while also guaranteeing the communication network of the MAS to be robustly connected at all times. Additionally, we provide a data-based methodology to estimate the disturbances sets required by the robust MPC formulation. The results are demonstrated with experiments in two obstacle-filled scenarios.

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Section: Connectivitymentioning

confidence: 88%

Section: Mpc-mip Motion Plannermentioning

confidence: 99%

Section: Mpc-mip Motion Plannermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming

Caregnato-Neto¹,

Máximo²,

Afonso³

2022

Preprint

Self Cite

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show abstract

“…It however neglects the dynamic constraints such as limited velocity and acceleration. Optimization-based methods such as [5], [20] directly formulate these constraints as mixed integer programs (MIP). However, the complexity increases drastically with the number of agents and obstacles, yielding it impractical for real-time applications.…”

Section: A Related Workmentioning

confidence: 99%

Online generation of safe trajectories for quadrotor UAV flight in cluttered environments

Chen¹

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A reliable communication network is essential for multiple UAVs operating within obstacle-cluttered environments, where limited communication due to obstructions often occurs. A common solution is to deploy intermediate UAVs to relay information via a multi-hop network, which introduces two challenges: (i) how to design the structure of multi-hop networks; and (ii) how to maintain connectivity during collaborative motion. To this end, this work first proposes an efficient constrained search method based on the minimum-edge RRT ⋆ algorithm, to find a spanning-tree topology that requires a less number of UAVs for the deployment task. To achieve this deployment, a distributed model predictive control strategy is proposed for the online motion coordination. It explicitly incorporates not only the inter-UAV and UAV-obstacle distance constraints, but also the line-of-sight (LOS) connectivity constraint. These constraints are well-known to be nonlinear and often tackled by various approximations. In contrast, this work provides a theoretical guarantee that all agent trajectories are ensured to be collisionfree with a team-wise LOS connectivity at all time. Numerous simulations are performed in 3D valley-like environments, while hardware experiments validate its dynamic adaptation when the deployment position changes online.

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Emergency repair strategy of distribution network under wind disaster based on multidimensional importance evaluation

Huang

et al. 2023

Energy Reports

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Resilient Robust Connectivity for Multiagent Systems with Line of Sight Using Mixed-Integer Programming

Cited by 6 publications

References 28 publications

Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming

Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming

Online generation of safe trajectories for quadrotor UAV flight in cluttered environments

Emergency repair strategy of distribution network under wind disaster based on multidimensional importance evaluation

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