Occupancy grid based distributed MPC for mobile robots

Mehrez, Mohamed W.; Sprodowski, Tobias; Worthmann, Karl; Mann, George K. I.; Gosine, Raymond G.; Sagawa, Juliana Keiko; Pannek, Jürgen

doi:10.1109/iros.2017.8206360

Cited by 12 publications

(10 citation statements)

References 18 publications

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“…Another recent relevant work on Distributed MPC for MRS is presented in [19]. Instead of relying on complete predictions of other robots trajectories it uses occupancy grid data aiming for a reduction in the required communication means.…”

Section: Related Workmentioning

confidence: 99%

Experimental Validation of a Multirobot Distributed Receding Horizon Motion Planning Approach

Filho

Lucet²,

Filliat

2018

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Related Workmentioning

confidence: 99%

Experimental Validation of a Multirobot Distributed Receding Horizon Motion Planning Approach

Filho

Lucet²,

Filliat

2018

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)

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“…The predicted trajectories are quantised obtaining grid indices and used to communicate them between the robots. This approach, introduced in References [9,10], allows to keep the problem suitable for optimisation algorithms in a continuous setting while taking advantage in the communication reduction via discretisation. The optimisation and therefore the communication is carried out in a sequential manner according to Reference [11]; the future predicted state trajectories of each robot (here, discrete occupancy tuples) are communicated iteratively for each time instant.…”

Section: Introductionmentioning

confidence: 99%

“…The optimisation and therefore the communication is carried out in a sequential manner according to Reference [11]; the future predicted state trajectories of each robot (here, discrete occupancy tuples) are communicated iteratively for each time instant. While in the former work [9,10] conditions considering initial and recursive feasibility were examined, the focus here is set to derive conditions for convergence and practical stability of the overall system.…”

Section: Introductionmentioning

confidence: 99%

Analytical Aspects of Distributed MPC Based on an Occupancy Grid for Mobile Robots

Sprodowski

Pannek

2020

Applied Sciences

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In this paper, we evaluate theoretical aspects of a distributed system of noncooperative robots controlled by a distributed model predictive control scheme, which operates in a shared space. Here, for collision avoidance, the future predicted state trajectories are projected on a grid and exchanged via discrete cell indexes to reduce the communication burden. The predicted trajectories are obtained locally by each robot and carried out in the continuous space. Therefore, the quantisation does not impose the quality of the solution. We derive sufficient conditions to show convergence and practical stability for the distributed control system by using an idea of a temporary roundabout derived from crossing patterns of street traffic rules, which is established in a fixed and flexible circle size. Furthermore, a condition for the sufficient prediction horizon length to recognise necessary detours is presented, which is adapted for the occupancy grid. The theoretical results match with the trajectory patterns from former numerical simulations, showing that this pattern is naturally chosen as an overall solution.

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“…The majority of results on distributed optimization investigates convex problems [1,2,5]. Many practically relevant problems, however, are inherently non-convex; examples range from non-linear model predictive control [6,7] to power systems [8][9][10] and wireless sensor networks [11].…”

Section: Introductionmentioning

confidence: 99%

Decomposition of non-convex optimization via bi-level distributed ALADIN

Engelmann¹,

Jiang²,

Houska³

et al. 2019

Preprint

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Decentralized optimization algorithms are important in different contexts, such as distributed optimal power flow or distributed model predictive control, as they avoid central coordination and enable decomposition of large-scale problems. In case of constrained non-convex optimization only a few algorithms are currently are available; often their performance is limited, or they lack convergence guarantees. This paper proposes a framework for decentralized non-convex optimization via bi-level distribution of the Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) algorithm. Bi-level distribution means that the outer ALADIN structure is combined with an inner distribution/decentralization level solving a condensed variant of ALADIN's convex coordination QP by decentralized algorithms. We prove sufficient conditions ensuring local convergence while allowing for inexact decentralized/distributed solutions of the coordination QP. Moreover, we show how a decentralized variant of conjugate gradient or decentralized ADMM schemes can be employed at the inner level. We draw upon case studies from power systems and robotics to illustrate the performance of the proposed framework.

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Occupancy grid based distributed MPC for mobile robots

Cited by 12 publications

References 18 publications

Experimental Validation of a Multirobot Distributed Receding Horizon Motion Planning Approach

Experimental Validation of a Multirobot Distributed Receding Horizon Motion Planning Approach

Analytical Aspects of Distributed MPC Based on an Occupancy Grid for Mobile Robots

Decomposition of non-convex optimization via bi-level distributed ALADIN

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