Experimenting with robotic intra-logistics domains

Gebser, Martin; Obermeier, Philipp; Otto, T.; Schaub, Torsten; Sabuncu, Orkunt; Nguyen, Van Duc; Son, Tran Cao

doi:10.1017/s1471068418000200

Cited by 18 publications

(22 citation statements)

References 14 publications

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“…For our experimental studies, we use benchmarks from the domain of robotic intra-logistics stemming from the asprilo framework [23]. As illustrated in Figure 6 and 7, we consider grids of size 7×7 with n ∈ {2, 3} robots and n * 2 orders of single products, each located on a unique shelf.…”

Section: Discussionmentioning

confidence: 99%

Automata for dynamic answer set solving: Preliminary report

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Diéguez,

Hahn

et al. 2021

Preprint

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We explore different ways of implementing temporal constraints expressed in an extension of Answer Set Programming (ASP) with language constructs from dynamic logic. Foremost, we investigate how automata can be used for enforcing such constraints. The idea is to transform a dynamic constraint into an automaton expressed in terms of a logic program that enforces the satisfaction of the original constraint. What makes this approach attractive is its independence of time stamps and the potential to detect unsatisfiability. On the one hand, we elaborate upon a transformation of dynamic formulas into alternating automata that relies on meta-programming in ASP. This is the first application of reification applied to theory expressions in gringo. On the other hand, we propose two transformations of dynamic formulas into monadic second-order formulas. These can then be used by off-the-shelf tools to construct the corresponding automata. We contrast both approaches empirically with the one of the temporal ASP solver telingo that directly maps dynamic constraints to logic programs. Since this preliminary study is restricted to dynamic formulas in integrity constraints, its implementations and (empirical) results readily apply to conventional linear dynamic logic, too.

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Section: Discussionmentioning

confidence: 99%

Automata for dynamic answer set solving: Preliminary report

Cabalar,

Diéguez,

Hahn

et al. 2021

Preprint

Self Cite

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“…The uses of these programs are controlled by a C++ implementation. First, given a MAPF problem P, as generated by the ASPRILO project [6], and the dimension dx × dy of desired subproblems, program base is called to determine the following atoms:…”

Section: Problem Divisionmentioning

confidence: 99%

“…The program shown in figure 5 is used by every active solver to make a movement plan for its area that exists some robot that has not reached its goal or assigned border yet. It is similar to the encoding used by the ASPRILO project [6], except that it has the following constraints:…”

Section: Movement Planningmentioning

confidence: 99%

“…The problem is called Multi-Agent Path Finding (MAPF) and will be formally introduced in Section 2.1. Most existing MAPF algorithms are centralized (i.e., having a central unit overseeing the entire solving process) such as WHCA* [13], asprilo [6], and CBS [12]. While there are attempts to improve the scalability of centralized algorithms using various techniques, such as abstraction (e.g., planning for each agent independently then combine the partial plans to obtain the solution -while resolving any conflict), dealing with MAPF problems with a large number of agents (greater than a thousand) still remains a challenge.…”

Section: Introductionmentioning

confidence: 99%

“…DMAPF is able to take advantage of distributed computing to cope with the possibility of having an ever-increasing problem size. An input problem to DMAPF is encoded in answer set program as generated by the AS-PRILO project [6] and solved using mainly the answer set programming, which will be introduced in Section 2.2. The communication between distributed components in DMAPF is facilitated by the Robot Operating System (ROS), which will be introduced in Section 2.3.…”

Section: Introductionmentioning

confidence: 99%

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DMAPF: A Decentralized and Distributed Solver for Multi-Agent Path Finding Problem with Obstacles

Pianpak¹,

Son²

2021

Electron. Proc. Theor. Comput. Sci.

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Multi-Agent Path Finding (MAPF) is a problem of finding a sequence of movements for agents to reach their assigned location without collision. Centralized algorithms usually give optimal solutions, but have difficulties to scale without employing various techniques -usually with a sacrifice of optimality; but solving MAPF problems with the number of agents greater than a thousand remains a challenge nevertheless. To tackle the scalability issue, we present DMAPF -a decentralized and distributed MAPF solver, which is a continuation of our recently published work, ros-dmapf [10]. We address the issues of ros-dmapf where it (i) only works in maps without obstacles; and (ii) has a low success rate with dense maps. Given a MAPF problem, both ros-dmapf and DMAPF divide the map spatially into subproblems, but the latter further divides each subproblem into disconnected regions called areas. Each subproblem is assigned to a distributed solver, which then individually creates an abstract plan -a sequence of areas that an agent needs to visit -for each agent in it, and interleaves agent migration with movement planning. Answer Set Programming, which is known for its performance in small but complex problems, is used in many parts including problem division, abstract planning, border assignment for the migration, and movement planning. Robot Operating System is used to facilitate communication between the solvers and to enable the opportunity to integrate with robotic systems. DMAPF introduces a new interaction protocol between the solvers, and mechanisms that together result in a higher success rate and better solution quality without sacrificing much of the performance. We implement and experimentally validate DMAPF by comparing it with other state-of-the-art MAPF solvers and the results show that our system achieves better scalability.

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