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30
DistanceOptimal Navigation in an Unknown Environment without Sensing Distances
 IEEE TRANSACTIONS ON ROBOTICS
"... This paper considers what can be accomplished using a mobile robot that has limited sensing. For navigation and mapping, the robot has only one sensor, which tracks the directions of depth discontinuities. There are no coordinates, and the robot is given a motion primitive that allows it to move t ..."
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Cited by 43 (17 self)
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This paper considers what can be accomplished using a mobile robot that has limited sensing. For navigation and mapping, the robot has only one sensor, which tracks the directions of depth discontinuities. There are no coordinates, and the robot is given a motion primitive that allows it to move toward discontinuities. The robot is incapable of performing localization or measuring any distances or angles. Nevertheless, when dropped into an unknown planar environment, the robot builds a data structure, called the Gap Navigation Tree, which enables it to navigate optimally in terms of Euclidean distance traveled. In a sense, the robot is able to learn the critical information contained in the classical shortestpath roadmap, although surprisingly it is unable to extract metric information. We prove these results for the case of a point robot placed into a simply connected, piecewiseanalytic planar environment. The case of multiply connected environments is also addressed, in which it is shown that further sensing assumptions are needed. Due to the limited sensor given to the robot, globally optimal navigation is impossible; however, our approach achieves locally optimal (within a homotopy class) navigation, which is the best that is theoretically possible under this robot model.
PursuitEvasion on Trees by Robot Teams
, 2010
"... We present GraphClear, a novel pursuitevasion problem on graphs which models the detection of intruders in complex indoor environments by robot teams. The environment is represented by a graph, and a robot team can execute sweep and block actions on vertices and edges respectively. A sweep action ..."
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Cited by 25 (4 self)
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We present GraphClear, a novel pursuitevasion problem on graphs which models the detection of intruders in complex indoor environments by robot teams. The environment is represented by a graph, and a robot team can execute sweep and block actions on vertices and edges respectively. A sweep action detects intruders in a vertex and represents the capability of the robot team to detect intruders in the region associated to the vertex. Similarly, a block action prevents intruders from crossing an edge and represents the capability to detect intruders as they move between regions. Both actions may require multiple robots to be executed. A strategy is a sequence of block and sweep actions detecting all intruders. When solving instances of GraphClear the goal is to determine optimal strategies, i.e. strategies using the least number of robots. We prove that for the general case of graphs the problem of computing optimal strategies is NPhard. Next, for the special case of trees we provide a polynomial time algorithm. The algorithm ensures that throughout the execution of the strategy all cleared vertices form a connected subtree, and we show it produces optimal strategies.
VisibilityBased PursuitEvasion with Bounded Speed
"... This paper presents an algorithm for a visibilitybased pursuitevasion problem in which bounds on the speeds of the pursuer and evader are given. The pursuer tries to find the evader inside of a simplyconnected polygonal environment, and the evader in turn tries actively to avoid detection. The ..."
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Cited by 23 (1 self)
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This paper presents an algorithm for a visibilitybased pursuitevasion problem in which bounds on the speeds of the pursuer and evader are given. The pursuer tries to find the evader inside of a simplyconnected polygonal environment, and the evader in turn tries actively to avoid detection. The algorithm is at least as powerful as the complete algorithm for the unbounded speed case, and with the knowledge of speed bounds, generates solutions for environments that were previously unsolvable. Furthermore, the paper develops a characterization of the set of possible evader positions as a function of time. This characterization is more complex than in the unboundspeed case, because it no longer depends only on the combinatorial changes in the visibility region of the pursuer.
Lessons learned in integration for sensorbased robot navigation systems
 International Journal of Advanced Robotic Systems
"... Abstract: This paper presents our work of integration during the last years within the context of sensor‐based robot navigation systems. In our motion system, as in many others, there are functionalities involved such as modeling, planning or motion control, which have to be integrated within an arc ..."
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Cited by 20 (13 self)
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Abstract: This paper presents our work of integration during the last years within the context of sensor‐based robot navigation systems. In our motion system, as in many others, there are functionalities involved such as modeling, planning or motion control, which have to be integrated within an architecture. This paper addresses this problematic. Furthermore, we also discuss the lessons learned while: (i) designing, testing and validating techniques that implement the functionalities of the navigation system, (ii) building the architecture of integration, and (iii) using the system on several robots equipped with different sensors in different laboratories. Keywords: Mobile robots, Sensor‐Based Robot Navigation, Robot Architectures and Integration. 1.
Bitbots: Simple robots solving complex tasks
 In AAAI National Conference on Artificial Intelligence
, 2005
"... Sensing uncertainty is a central issue in robotics. Sensor limitations often prevent accurate state estimation, and robots find themselves confronted with a complicated information (belief) space. In this paper we define and characterize the information spaces of very simple robots, called Bitbots ..."
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Cited by 16 (7 self)
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Sensing uncertainty is a central issue in robotics. Sensor limitations often prevent accurate state estimation, and robots find themselves confronted with a complicated information (belief) space. In this paper we define and characterize the information spaces of very simple robots, called Bitbots, which have severe sensor limitations. While complete estimation of the robot’s state is impossible, careful consideration and management of the uncertainty is presented as a search in the information space. We show that these simple robots can solve several challenging online problems, even though they can neither obtain a complete map of their environment nor exactly localize themselves. However, when placed in an unknown environment, Bitbots can build a topological representation of it and then perform pursuitevasion (i.e., locate all moving targets inside this environment). This paper introduces Bitbots, and provides both theoretical analysis of their information spaces and simulation results.
On comparing the power of robots
 International Journal of Robotics Research. Under review
"... Robots must complete their tasks in spite of unreliable actuators and limited, noisy sensing. In this paper, we consider the information requirements of such tasks. What sensing and actuation abilities are needed to complete a given task? Are some robot systems provably “more powerful, ” in terms of ..."
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Cited by 15 (7 self)
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Robots must complete their tasks in spite of unreliable actuators and limited, noisy sensing. In this paper, we consider the information requirements of such tasks. What sensing and actuation abilities are needed to complete a given task? Are some robot systems provably “more powerful, ” in terms of the tasks they can complete, than others? Can we find meaningful equivalence classes of robot systems? This line of research is inspired by the theory of computation, which has produced similar results for abstract computing machines. The basic idea is a dominance relation over robot systems that formalizes the idea that some robots are stronger than others. This comparison, which is based on the how the robots progress through their information spaces, induces a partial order over the set of robot systems. We prove some basic properties of this partial order and show that it is directly related to the robots’ ability to complete tasks. We give examples to demonstrate the theory, including a detailed analysis of a limitedsensing global localization problem. 1
Localization with limited sensing
 IEEE Transations on Robotics
, 2007
"... Abstract — Localization is a fundamental problem for many kinds of mobile robots. Sensor systems of varying ability have been proposed and successfully used to solve the problem. This paper probes the lower limits of this range by describing three extremely simple robot models and addressing the act ..."
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Cited by 10 (6 self)
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Abstract — Localization is a fundamental problem for many kinds of mobile robots. Sensor systems of varying ability have been proposed and successfully used to solve the problem. This paper probes the lower limits of this range by describing three extremely simple robot models and addressing the active localization problem for each. The robot, whose configuration is composed of its position and orientation, moves in a fully known simply connected polygonal environment. We pose the localization task as a planning problem in the robot’s information space, which encapsulates the uncertainty in the robot’s configuration. We consider robots equipped with (1) angular and linear odometers, (2) a compass and contact sensor, and (3) an angular odometer and contact sensor. We present localization algorithms for models 1 and 2 and show that no algorithm exists for model 3. An implementation with simulation examples is presented. Index Terms — information spaces, mobile robot localization, robots, robot sensing systems I.
Information spaces for mobile robots
 in Proc. Int. Work. on
, 2005
"... Planning with sensing uncertainty is central to robotics. Sensor limitations often prevent accurate state estimation of the robot. Two general approaches can be taken for solving robotics tasks given sensing uncertainty. The first approach is to estimate the state and to solve the given task using t ..."
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Cited by 6 (0 self)
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Planning with sensing uncertainty is central to robotics. Sensor limitations often prevent accurate state estimation of the robot. Two general approaches can be taken for solving robotics tasks given sensing uncertainty. The first approach is to estimate the state and to solve the given task using the estimate as the real state. However, estimation of the state may sometimes be harder than solving the original task. The other approach is to avoid estimation of the state, which can be achieved by defining the information space, the space of all histories of actions and sensing observations of a robot system. Considering information spaces brings better understanding of problems involving uncertainty, and also allows finding better solutions to such problems. In this paper we give a brief description of the information space framework, followed by its use in some robotic tasks. 1
Discovering a point source in unknown environments
 in “Algorithmic Foundation of Robotics VII
, 2009
"... Abstract: We consider the inverse problem of discovering the location of a source from very sparse point measurements in a bounded domain that contains impenetrable (and possibly unknown) obstacles. We present an adaptive algorithm for determining the measurement locations, and ultimately, the sour ..."
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Cited by 6 (0 self)
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Abstract: We consider the inverse problem of discovering the location of a source from very sparse point measurements in a bounded domain that contains impenetrable (and possibly unknown) obstacles. We present an adaptive algorithm for determining the measurement locations, and ultimately, the source locations. Specifically, we investigate source discovery for the Laplace operator, though the approach can be applied to more general linear partial differential operators. We propose a strategy for the case when the obstacles are unknown and the environment has to be mapped out using a range sensor concurrently with source discovery. 1
Autonomous exploration using rapid perception of lowresolution image information
 Autonomous Robots
"... We present a technique for mobile robot exploration in unknown indoor environments using only a single forwardfacing camera. Rather than processing all the data, the method intermittently examines only small 32 ×24 downsampled grayscale images. We show that for the task of indoor exploration the vi ..."
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Cited by 4 (1 self)
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We present a technique for mobile robot exploration in unknown indoor environments using only a single forwardfacing camera. Rather than processing all the data, the method intermittently examines only small 32 ×24 downsampled grayscale images. We show that for the task of indoor exploration the visual information is highly redundant, allowing successful navigation even using only a small fraction of the available data. The method keeps the robot centered in the corridor by estimating two state parameters: the orientation within the corridor, and the distance to the end of the corridor. The orientation is determined by combining the results of five complementary measures, while the estimated distance to the end combines the results of three complementary measures. These measures, which are predominantly informationtheoretic, are analyzed independently, and the combined system is tested in several unknown corridor buildings exhibiting a wide variety of appearances, showing the sufficiency of lowresolution visual information for mobile robot exploration. Because the algorithm discards such a large percentage of the pixels both spatially and temporally, processing occurs at an average of 1000 frames per second, thus freeing the processor for other concurrent tasks. 1