Multirobot Tree and Graph Exploration

Networks, 2006

An Ò-node tree has to be explored by mobile agents (robots), starting in its root. Every edge of the tree must be traversed by at least one robot, and exploration must be completed as fast as possible. Even when the tree is known in advance, scheduling optimal collective exploration turns out to be NP-hard. We investigate the problem of distributed collective exploration of unknown trees. Not surprisingly, communication between robots influences the time of exploration. Our main communication scenario is the following: robots can communicate by writing at the currently visited node previously acquired information, and reading information available at this node. We construct an exploration algorithm whose running time for any tree is only Ç´ ÐÓ µ larger than optimal exploration time with full knowledge of the tree. (We say that the algorithm has overhead Ç´ ÐÓ µ). On the other hand we show that, in order to get overhead sublinear in the number of robots, some communication is necessary. Indeed, we prove that if robots cannot communicate at all, then every distributed exploration algorithm works in time ª´ µ larger than optimal exploration time with full knowledge, for some trees.

In the effort to understand the algorithmic limitations of computing by a swarm of robots, the research has focused on the minimal capabilities that allow a problem to be solved. The weakest of the commonly used models is Asynch where the autonomous mobile robots, endowed with visibility sensors (but otherwise unable to communicate), operate in Look-Compute-Move cycles performed asynchronously for each robot. The robots are often assumed (or required to be) oblivious: they keep no memory of observations and computations made in previous cycles. We consider the setting when the robots are dispersed in an anonymous and unlabeled graph, and they must perform the very basic task of exploration: within finite time every node must be visited by at least one robot and the robots must enter a quiescent state. The complexity measure of a solution is the number of robots used to perform the task. We study the case when the graph is an arbitrary tree and establish some unexpected results. We first prove that there are n-node trees where Ω(n) robots are necessary; this holds even if the maximum degree is 4. On the other hand, we show that if the maximum degree is 3, it is possible to explore with only O( log n log log n ) robots. The proof of the result is constructive. Finally, we prove that the size of the team is asymptotically optimal: we show that there are trees of degree 3 whose exploration requires Ω( log n log log n ) robots.

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017

In this paper, we present a complete algorithm for exploration of unknown environments containing disjoint obstacles with multiple robots. We propose a distributed approach considering two main cases. In the first one, the obstacles are distinguishable, i.e., each obstacle is uniquely identifiable, which can be imagined as each obstacle having a different color, and in the second case, the obstacles are not distinguishable. Two possible applications of our algorithms are: 1) Search of a static object in an unknown environment. 2) Damage verification in unknown environments composed by multiple elements (e.g. buildings). The main contributions of this work are the following: 1) The algorithms guarantee exploring the whole environment in finite time even though each robot does not have full information about the part of the environment explored by other robots. 2) The method only requires limited communication between the robots. In both cases distinguishable and indistinguishable obstacles, the robots communicate only at rendezvous. 3) The algorithm scales well to hundreds of robots and obstacles. We tested in several simulations the performance of our algorithms for both cases, in terms of the distance traveled by the robots.

Proceedinbgs of the 24th ACM symposium on Parallelism in algorithms and architectures - SPAA '12, 2012

We consider the multi-robot exploration problem of an unknown n × n grid graph with oriented disjoint rectangular obstacles. All robots start at a given node and have to visit all nodes of the graph. The robots are unrestricted in their computational power and storage. In the local communication model the robots can exchange any information if they meet at the same node. In the global communication model all robots share the same knowledge. In this paper we present the first nontrivial upper and lower bounds. We show that k robots can explore the graph using only local communication in time O(n log 2 (n) + (f log n)/k), where f is the number of free nodes in the graph. This establishes a competitive upper bound of O(log 2 n). For the lower bound we show a competitive factor of Ω log k log log k for deterministic exploration and Ω √ log k log log k for randomized exploration strategies using global communication.

2010 IEEE International Conference on Robotics and Automation, 2010

In this paper we study the problem of multi-robot exploration of unknown indoor environments that are modeled as trees. Specifically, our approach consider that robots deploy and communicate with active landmarks in every intersection they encounter. We present a novel algorithm that is guaranteed to completely explore any tree with m edges and diameter D, by allowing k robots to be fed into the tree one at a time. We prove that the exploration time of the algorithm grows in linear proportion with the size of the tree and is not bigger than D + m. Simulation results are presented that corroborate the theoretical analysis.

2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008

This paper addresses the problem of exploring an unknown environment with a team of mobile robots. The key issue in coordinated multi-robot exploration is how to assign target locations to the individual robots such that the overall mission time is minimized. In this paper, we propose a novel approach to distribute the robots over the environment that takes into account the structure of the environment. To achieve this, it partitions the space into segments, for example, corresponding to individual rooms. Instead of only selecting frontiers between unknown and explored areas as target locations, we send the robots to the individual segments with the task to explore the corresponding area. Our approach has been implemented and tested in simulation as well as in real world experiments. The experiments demonstrate that the overall exploration time can be significantly reduced by considering the segmentation of the environment.

2002

In this paper we consider the problem of exploring an unknown environment by a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved in the context of multiple robots is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of the environment. We present an approach for the coordination of multiple robots which, in contrast to previous approaches, simultaneously takes into account the cost of reaching a target point and its utility. The utility of a target point is given by the size of the unexplored area that a robot can cover with its sensors upon reaching that location. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced for the other robots. This way, a team of multiple robots assigns different target points to the individual robots. The technique has been implemented and tested extensively in real-world experiments and simulation runs. The results given in this paper demonstrate that our coordination technique significantly reduces the exploration time compared to previous approaches.

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

A multi-robotic exploration with the requirement of communication link to a fixed base station is presented in this paper. The robots organize themselves into roles of maintainers of communication (hinged robots or robot nodes) or explorers of the environment ensuring that every robot is in contact with the base station directly or through the hinged robots. A two phased strategy for the same is presented. The first phase is characterized by a recursive growth of trees that starts from the root node or the base station and then repeated from other nodes of the hitherto grown tree in a depth first fashion. The second phase constitutes the recursive tree growth invoked repeatedly from the frontier nodes. While the first phase rapidly explores areas around the base station in a concentric fashion, the second phase extends the depth of the explored area to increase the limits of coverage. The strategy is consistent in that none of the robots loose contact with the base station. Extensive simulations confirm the efficacy of the method and comparisons portray performance gain in terms of exploration time and absence of deadlocks visa -vis the few methods previously reported in the literature.

IEEE Transactions on Robotics, 2000

In this paper, we consider the problem of exploring an unknown environment with a team of robots. As in singlerobot exploration the goal is to minimize the overall exploration time. The key problem to be solved in the context of multiple robots is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of the environment. We present an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced. In this way, different target locations are assigned to the individual robots. We furthermore describe how our algorithm can be extended to situations in which the communication range of the robots is limited. Our technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission.

Exploration of initially unknown environments is a fundamental task in several robot applications, like search and rescue and map building. In the literature, many works propose exploration strategies that allow multiple mobile robots to autonomously select the next observation locations in order to incrementally discover the environment in an efficient way. The effects of realistic communication between robots have been considered by some papers that account for communication constraints in the design of exploration strategies. However, these approaches have not been comparatively assessed yet. In this paper, we briefly review the relevant literature of communication-constrained exploration strategies and present an experimental quantitative comparison of some of them.