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175
Collaborative Multi-Robot Exploration
- IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2000
, 2000
"... 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 therefore is to choose appropriate target points for the individual robots so that they sim ..."
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Cited by 276 (31 self)
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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 therefore is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of their environment. We present a probabilistic approach for the coordination of multiple robots which, in contrast to previous approaches, simultaneously takes into account the costs of reaching a target point and the utility of target points. The utility of target points is given by the size of the unexplored area that a robot can cover with its sensors upon reaching a target position. 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.
Multi-robot exploration controlled by a market economy
, 2002
"... This work presents a novel approach to efficient multirobot mapping and exploration which exploits a market architecture in order to maximize information gain while minimizing incurred costs. This system is reliable and robust in that it can accommodate dynamic introduction and loss of team members ..."
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Cited by 185 (16 self)
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This work presents a novel approach to efficient multirobot mapping and exploration which exploits a market architecture in order to maximize information gain while minimizing incurred costs. This system is reliable and robust in that it can accommodate dynamic introduction and loss of team members in addition to being able to withstand communication interruptions and failures. Results showing the capabilities of our system on a team of exploring autonomous robots are given. 1
Coordination for multi-robot exploration and mapping
- IN PROCEEDINGS OF THE AAAI NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 2000
"... This paper addresses the problem of exploration and mapping of an unknown environment by multiple robots. The mapping algorithm is an on-line approach to likelihood maximization that uses hill climbing to find maps that are maximally consistent with sensor data and odometry. The exploration algorith ..."
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Cited by 169 (25 self)
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This paper addresses the problem of exploration and mapping of an unknown environment by multiple robots. The mapping algorithm is an on-line approach to likelihood maximization that uses hill climbing to find maps that are maximally consistent with sensor data and odometry. The exploration algorithm explicitly coordinates the robots. It tries to maximize overall utility by minimizing the potential for overlap in information gain amongst the various robots. For both the exploration and mapping algorithms, most of the computations are distributed. The techniques have been tested extensively in real-world trials and simulations. The results demonstrate the performance improvements and robustness that accrue from our multirobot approach to exploration.
Coordinated Multi-Robot Exploration
- IEEE Transactions on Robotics
, 2005
"... 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 individu ..."
Abstract
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Cited by 158 (10 self)
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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.
Information gain-based exploration using Rao-Blackwellized particle filters
- In RSS
, 2005
"... Abstract — This paper presents an integrated approach to exploration, mapping, and localization. Our algorithm uses a highly efficient Rao-Blackwellized particle filter to represent the posterior about maps and poses. It applies a decision-theoretic framework which simultaneously considers the uncer ..."
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Cited by 103 (4 self)
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Abstract — This paper presents an integrated approach to exploration, mapping, and localization. Our algorithm uses a highly efficient Rao-Blackwellized particle filter to represent the posterior about maps and poses. It applies a decision-theoretic framework which simultaneously considers the uncertainty in the map and in the pose of the vehicle to evaluate potential actions. Thereby, it trades off the cost of executing an action with the expected information gain and takes into account possible sensor measurements gathered along the path taken by the robot. We furthermore describe how to utilize the properties of the Rao-Blackwellization to efficiently compute the expected information gain. We present experimental results obtained in the real world and in simulation to demonstrate the effectiveness of our approach. I.
A practical, decision-theoretic approach to multi-robot mapping and exploration
- In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS
, 2003
"... An important assumption underlying virtually all approaches to multi-robot exploration is prior knowledge about their relative locations. This is due to the fact that robots need to merge their maps so as to coordinate their exploration strategies. The key step in map merging is to estimate the rela ..."
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Cited by 69 (5 self)
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An important assumption underlying virtually all approaches to multi-robot exploration is prior knowledge about their relative locations. This is due to the fact that robots need to merge their maps so as to coordinate their exploration strategies. The key step in map merging is to estimate the relative locations of the individual robots. This paper presents a novel approach to multi-robot map merging under global uncertainty about the robot’s relative locations. Our approach uses an adapted version of particle filters to estimate the position of one robot in the other robot’s partial map. The risk of false-positive map matches is avoided by verifying match hypotheses using a rendezvous approach. We show how to seamlessly integrate this approach into a decision-theoretic multi-robot coordination strategy. The experiments show that our sample-based technique can reliably find good hypotheses for map matches. Furthermore, we present results obtained with two robots successfully merging their maps using the decision-theoretic rendezvous strategy. 1
Distributed multi-robot exploration and mapping
- In Proceedings of the IEEE
, 2006
"... Abstract — Efficient exploration of unknown environments is a fundamental problem in mobile robotics. In this paper we present an approach to distributed multi-robot mapping and exploration. Our system enables teams of robots to efficiently explore environments from different, unknown locations. In ..."
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Cited by 53 (1 self)
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Abstract — Efficient exploration of unknown environments is a fundamental problem in mobile robotics. In this paper we present an approach to distributed multi-robot mapping and exploration. Our system enables teams of robots to efficiently explore environments from different, unknown locations. In order to ensure consistency when combining their data into shared maps, the robots actively seek to verify their relative locations. Using shared maps, they coordinate their exploration strategies so as to maximize the efficiency of exploration. Our system was evaluated under extremely realistic real-world conditions. An outside evaluation team found the system to be highly efficient and robust. The maps generated by our approach are consistently more accurate than those generated by manually measuring the locations and extensions of rooms and objects. I.
Stupid Robot Tricks: A Behavior-Based Distributed Algorithm Library for Programming Swarms of Robots
, 2004
"... by.......................................................................................... ..."
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Cited by 52 (8 self)
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Map merging for distributed robot navigation
- In Intl. Conf. on Intelligent Robots and Systems
, 2003
"... A set of robots mapping an area can potentially combine their information to produce a distributed map more efficiently than a single robot alone. We describe a general framework for distributed map building in the presence of uncertain communication. Within this framework, we then present a technic ..."
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Cited by 39 (0 self)
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A set of robots mapping an area can potentially combine their information to produce a distributed map more efficiently than a single robot alone. We describe a general framework for distributed map building in the presence of uncertain communication. Within this framework, we then present a technical solution to the key decision problem of determining relative location within partial maps. 1
Exploration with Active Loop-Closing for FastSLAM
, 2004
"... Acquiring models of the environment belongs to the fundamental tasks of mobile robots. In the last few years several researchers have focused on the problem of simultaneous localization and mapping (SLAM). Classic SLAM approaches are passive in the sense that they only process the perceived sensor d ..."
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Cited by 36 (2 self)
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Acquiring models of the environment belongs to the fundamental tasks of mobile robots. In the last few years several researchers have focused on the problem of simultaneous localization and mapping (SLAM). Classic SLAM approaches are passive in the sense that they only process the perceived sensor data and do not influence the motion of the mobile robot. In this paper we present a novel and integrated approach that combines autonomous exploration with simultaneous localization and mapping. Our method uses a grid-based version of the FastSLAM algorithm and at each point in time considers actions to actively close loops during exploration. By re-entering already visited areas the robot reduces its localization error and this way learns more accurate maps. Experimental results presented in this paper illustrate the advantage of our method over pervious approaches lacking the ability to actively close loops.
