Integrated Intelligent Computing, Communication and Security, 2018
Extended Conflict-Based Search (XCBS) is a distributed agent-based approach which has been used f... more Extended Conflict-Based Search (XCBS) is a distributed agent-based approach which has been used for path finding and scheduling of spatially extended agents on a traversable network. The algorithm arrives at an optimal schedule while resolving conflicts between pairs of agents one at a time. In this chapter, we propose XCBS with Awareness wherein a conflicting agent plan is resolved with respect to the proposed route plan of other agents. The approach allows multiple conflicts to be resolved simultaneously, avoids cascading conflicts in the new plans and shows an improved efficiency in terms of nodes explored and time taken to arrive at the solution.
Path finding problems involve identification of a plan for conflict free movement of agents over ... more Path finding problems involve identification of a plan for conflict free movement of agents over a common road network. Most approaches to this problem handle the agents as point objects, wherein the size of the agent is significantly smaller than the road on which it travels. In this paper, we consider spatially extended agents which have a size comparable to the length of the road on which they travel. An optimal multi agent path finding approach for spatially-extended agents was proposed in the eXtended Conflict Based Search (XCBS) algorithm. As XCBS resolves only a pair of conflicts at a time, it results in deeper search trees in case of cascading or multiple (more than two agent) conflicts at a given location. This issue is addressed in eXtended Conflict Based Search with Awareness (XCBS-A) in which an agent uses awareness of other agents' plans to make its own plan. In this paper, we explore XCBS-A in greater detail, we theoretically prove its completeness and empirically ...
Multi Agent Path Finding (MAPF) requires identification of conflict free paths for agents which c... more Multi Agent Path Finding (MAPF) requires identification of conflict free paths for agents which could be point-sized or with dimensions. In this paper, we propose an approach for MAPF for spatially-extended agents. These find application in real world problems like Convoy Movement Problem, Train Scheduling etc. Our proposed approach, Decentralised Multi Agent Path Finding (DeMAPF), handles MAPF as a sequence of pathplanning and allocation problems which are solved by two sets of agents Travellers and Routers respectively, over multiple iterations. The approach being decentralised allows an agent to solve the problem pertinent to itself, without being aware of other agents in the same set. This allows the agents to be executed on independent machines, thereby leading to scalability to handle large sized problems. We prove, by comparison with other distributed approaches, that the approach leads to a faster convergence to a conflict-free solution, which may be suboptimal, with lesser ...
The Convoy Movement Problem (CMP) is a common military scenario that requires a clash-free plan f... more The Convoy Movement Problem (CMP) is a common military scenario that requires a clash-free plan for moving large convoys from one location to another with constraints on time and space. This article proposes a distributed agent-based approach for CMP that meets most on-field deployment constraints. The solution is based on a multi-agent path-finding algorithm called conflict-based search (CBS) for point objects. Convoys can't be regarded as point objects: their length can be significantly longer than the edges on which they travel. Hence, a modification to the CBS algorithm makes it applicable to spatially extended objects. This eXtended CBS (XCBS) algorithm has been used to solve the CMP while meeting most of its constraints. The algorithm has been tested on road networks with as many as 40,000 vertices and 79,600 edges for 800 convoys.
Integrated Intelligent Computing, Communication and Security, 2018
Extended Conflict-Based Search (XCBS) is a distributed agent-based approach which has been used f... more Extended Conflict-Based Search (XCBS) is a distributed agent-based approach which has been used for path finding and scheduling of spatially extended agents on a traversable network. The algorithm arrives at an optimal schedule while resolving conflicts between pairs of agents one at a time. In this chapter, we propose XCBS with Awareness wherein a conflicting agent plan is resolved with respect to the proposed route plan of other agents. The approach allows multiple conflicts to be resolved simultaneously, avoids cascading conflicts in the new plans and shows an improved efficiency in terms of nodes explored and time taken to arrive at the solution.
Path finding problems involve identification of a plan for conflict free movement of agents over ... more Path finding problems involve identification of a plan for conflict free movement of agents over a common road network. Most approaches to this problem handle the agents as point objects, wherein the size of the agent is significantly smaller than the road on which it travels. In this paper, we consider spatially extended agents which have a size comparable to the length of the road on which they travel. An optimal multi agent path finding approach for spatially-extended agents was proposed in the eXtended Conflict Based Search (XCBS) algorithm. As XCBS resolves only a pair of conflicts at a time, it results in deeper search trees in case of cascading or multiple (more than two agent) conflicts at a given location. This issue is addressed in eXtended Conflict Based Search with Awareness (XCBS-A) in which an agent uses awareness of other agents' plans to make its own plan. In this paper, we explore XCBS-A in greater detail, we theoretically prove its completeness and empirically ...
Multi Agent Path Finding (MAPF) requires identification of conflict free paths for agents which c... more Multi Agent Path Finding (MAPF) requires identification of conflict free paths for agents which could be point-sized or with dimensions. In this paper, we propose an approach for MAPF for spatially-extended agents. These find application in real world problems like Convoy Movement Problem, Train Scheduling etc. Our proposed approach, Decentralised Multi Agent Path Finding (DeMAPF), handles MAPF as a sequence of pathplanning and allocation problems which are solved by two sets of agents Travellers and Routers respectively, over multiple iterations. The approach being decentralised allows an agent to solve the problem pertinent to itself, without being aware of other agents in the same set. This allows the agents to be executed on independent machines, thereby leading to scalability to handle large sized problems. We prove, by comparison with other distributed approaches, that the approach leads to a faster convergence to a conflict-free solution, which may be suboptimal, with lesser ...
The Convoy Movement Problem (CMP) is a common military scenario that requires a clash-free plan f... more The Convoy Movement Problem (CMP) is a common military scenario that requires a clash-free plan for moving large convoys from one location to another with constraints on time and space. This article proposes a distributed agent-based approach for CMP that meets most on-field deployment constraints. The solution is based on a multi-agent path-finding algorithm called conflict-based search (CBS) for point objects. Convoys can't be regarded as point objects: their length can be significantly longer than the edges on which they travel. Hence, a modification to the CBS algorithm makes it applicable to spatially extended objects. This eXtended CBS (XCBS) algorithm has been used to solve the CMP while meeting most of its constraints. The algorithm has been tested on road networks with as many as 40,000 vertices and 79,600 edges for 800 convoys.
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