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A comparative study of bug algorithms for robot navigation

ROBOTICS AND AUTONOMOUS SYSTEMS 2019年 121卷

作者： McGuire, K. N. de Croon, G. C. H. E. Tuyls, K. Delft Univ Technol Fac Aerosp Engn Delft Netherlands Delft Univ Technol Micro Air Vehicle Lab MAV Lab Delft Netherlands Univ Liverpool Comp Sci Liverpool Merseyside England Univ Liverpool Res Sch Elect Engn & Elect & Comp Sci Liverpool Merseyside England

This paper presents a literature survey and a comparative study of bug algorithms, with the goal of investigating their potential for robotic navigation. At first sight, these methods seem to provide an efficient navigation paradigm, ideal for implementations on tiny robots with limited resources. Closer inspection, however, shows that many of these bug algorithms assume perfect global position estimate of the robot which in GPS-denied environments implies considerable expenses of computation and memory - relying on accurate Simultaneous Localization And Mapping (SLAM) or Visual Odometry (VO) methods. We compare a selection of bug algorithms in a simulated robot and environment where they endure different types noise and failure-cases of their on-board sensors. From the simulation results, we conclude that the implemented bug algorithms' performances are sensitive to many types of sensor-noise, which was most noticeable for odometry-drift. This raises the question if bug algorithms are suitable for real-world, on-board, robotic navigation as is. Variations that use multiple sensors to keep track of their progress towards the goal, were more adept in completing their task in the presence of sensor-failures. This shows that bug algorithms must spread their risk, by relying on the readings of multiple sensors, to be suitable for real-world deployment. (C) 2019 Elsevier B.V. All rights reserved.

关键词： bug algorithms Robotic navigation Comparative study Limited sensing Indoor navigation

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Development and Analysis of an Improved Prototype within a Class of bug-based Heuristic Path Planners 30

Development and Analysis of an Improved Prototype within a C...

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30th IEEE International Symposium on Industrial Electronics (ISIE)

作者： Kai, Lai Yan Vadakkepat, Prahlad Al Mamun, Abdullah Cheng, Xiang Heng, Lee Tong Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore

ISBN: (纸本)9781728190235

Path planning relies on free-space expansions. The Ray Path Finder (RPF) and RayScan algorithms solve the Euclidean shortest path problem. Both rely on free-space expansions by basing on the bug concept, which is to cast rays to a desired target and trace any obstructing contours. By combining heuristic costs, an optimal path can be found. In this work, a new and insightful analysis aiding future designs of this class of heuristic bug-based planners is provided. A rigorous proof for a modified Pledge in RPF is included. A corrected RPF prototype is designed to compare with Anya, a state-of-the-art free-space planner. The computational advantages of the heuristic bug-baed planners can offer are provided.

关键词： Path Planning Euclidean Shortest Paths Any-angle bug algorithms Ray-casting

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A new hybrid navigation algorithm for mobile robots in environments with incomplete knowledge

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KNOWLEDGE-BASED SYSTEMS 2012年 27卷 302-313页

作者： Zhu, Yi Zhang, Tao Song, Jingyan Li, Xiaqin Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Tsinghua Natl Lab Informat Sci & Technol Div Control Sci & Engn Beijing 100084 Peoples R China Natl Key Lab Flight Vehicle Control Integrated Te Xian Peoples R China

Focusing on the navigation problem of mobile robots in environments with incomplete knowledge, a new hybrid navigation algorithm is proposed. The novel system architecture in the proposed algorithm is the main contribution of this paper. Unlike most existing hybrid navigation systems whose deliberative layers usually play the dominant role while the reactive layers are only simple executors, a more independent reactive layer that can guarantee convergence without the assistance of a deliberative layer is pursued in the proposed architecture, which brings two benefits. First, the burden of the deliberative layer is released, which is beneficial to guaranteeing real-time property and decreasing resource requirement. Second, some possible layer conflicts in the traditional architecture can be resolved, which improves the system stability. The convergence of the new algorithm has been proved. The simulation results show that compared with three traditional algorithms based on different architectures, the new hybrid navigation algorithm proposed in this paper performs more reliable in terms of escaping from traps, resolving conflicts between layers and decreasing the computational time for avoiding time out of the control cycle. The experiments on a real robot further verify the validity and applicability of the new algorithm. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Mobile robots Hybrid navigation Incomplete knowledge System architecture bug algorithms

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Visibility-based pursuit-evasion in an unknown planar environment

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INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2004年第1期23卷 3-26页

作者： Sachs, S LaValle, SM Rajko, S Univ Illinois Dept Comp Sci Urbana IL 61801 USA Iowa State Univ Dept Comp Sci Ames IA 50011 USA

We address an on-line version of the visibility-based pursuit-evasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simply-connected, piecewise-smooth planar environment, and is given the task of locating any unpredictable, moving evaders that have unbounded speed. The evaders are assumed to be points that move continuously. To solve the problem, the pursuer must for each target have an unobstructed view of it at some time during execution. The pursuer is equipped with a range sensor that measures the direction of depth discontinuities, but cannot provide precise depth measurements. All pursuer control is specified either in terms of this sensor or wall-following movements. The pursuer does not have localization capability or perfect control. We present a complete algorithm that enables the limited pursuer to clear the same environments that a pursuer with a complete map, perfect localization, and perfect control can clear (under certain general position assumptions). Theoretical guarantees that the evaders will be found are provided. The resulting algorithm to compute this strategy has been implemented in simulation. Results arc shown for several examples. The approach is efficient and simple enough to be useful towards the development of real robot systems that perform visual searching.

关键词： sensor-based planning visibility pursuit-evasion on-line algorithms surveillance bug algorithms sensing uncertainty

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Robust Navigation in an Unknown Environment With Minimal Sensing and Representation

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 2009年第1期39卷 212-229页

作者： Mastrogiovanni, Fulvio Sgorbissa, Antonio Zaccaria, Renato Univ Genoa Dept Commun Comp & Syst Sci I-16145 Genoa Italy

This paper presents mu Nav, a novel approach to navigation which, with minimal requirements in terms of onboard sensory, memory, and computational power, exhibits way-finding behaviors in very complex environments. The algorithm is intrinsically robust, since it does not require any internal geometrical representation or self-localization capabilities. Experimental results, performed with both simulated and real robots, validate the proposed theoretical approach.

关键词： bug algorithms minimal sensing navigation

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Distance-optimal navigation in an unknown environment without sensing distances

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IEEE TRANSACTIONS ON ROBOTICS 2007年第3期23卷 506-518页

作者： Tovar, Benjamin Murrieta-Cid, Rafael LaValle, Steven M. Univ Illinois Dept Comp Sci Urbana IL 61801 USA Ctr Math Res CIMAT Guanajuato 36000 Mexico

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 shortest-path 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, piecewise-analytic 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.

关键词： bug algorithms information spaces map building minimal sensing navigation optimality sensor-based planning shortest paths visibility

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Bioinspired Robot Path Planning using Pointbug Algorithm

Bioinspired Robot Path Planning using PointBug Algorithm

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Choudhury, Nupur Mandal, Rupesh Kar, Suman Kalyan Assam Don Bosco Univ Dept Comp Sci Engn & IT Gauhati India Sikkim Manipal Inst Technol Dept Comp Sci & Engn Sikkim India

ISBN: (纸本)9781467399395

This paper is an outcome of a research implementation that was carried out on a BOEbot (Board Of Education bot) existing in the robotics laboratory of Computer Science and Engineering Department of Sikkim Manipal Institute of Technology which resulted in the development of an essential algorithm that is primarily used to navigate a mobile robot in presence of a wide range of obstacles enabling the robot to move from starting location to a target location avoiding all the obstacles in between with the help of ultrasonic sensors. In order to achieve this it is utmost necessary to obtain a path that would avoid the obstacles that might be present in the static environments which in this paper is obtained using simple local path planning algorithm known as the Pointbug algorithm. Initially the algorithm determines the next point for the robot to move forward to the target from any current point which depicts the starting point in the beginning. The next point is determined by the output of the range sensors which depicts the nearest obstacle distance from the sensor which can also be termed as sudden change which can be considered as increasing or decreasing by a considerable value Delta d which needs to be defined with accuracy.

关键词： BOEBot bug algorithms robot navigation path planning pointbug

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A Minimalistic Quadrotor Navigation Strategy for Indoor Multi-floor Scenarios 13th

A Minimalistic Quadrotor Navigation Strategy for Indoor Mult...

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13th International Conference on Intelligent Autonomous Systems (IAS)

作者： Marino, Roberto Mastrogiovanni, Fulvio Sgorbissa, Antonio Zaccaria, Renato Univ Genoa Dept Informat Bioengn Robot & Syst Engn DIBRIS I-16145 Genoa Italy

ISBN: (纸本)9783319083384;9783319083377

This paper presents the application of a minimalistic navigation strategy, based on the well-known bug2 algorithm, to solve the problem of reaching a goal position in a multi-floor indoor scenario using a quadrotor. Examples of this scenario include buildings and in general cluttered indoor areas. As far as energy backup is concerned the quadrotor shows stricts constraints: for this reason implementing a low-consumption navigation strategy is a major issue. We present a two-layer navigation strategy, called MF-bug2, useful to navigate in multi-floor buildings starting from the ground floor toward the last or vice versa while searching for an interesting physical quantity (i.e,. gas leak, electromagnetic source). In the lower layer a bug-like algorithm is able to drive the flying robot, equipped with a salient-cue sensor and a laser-range-finder, toward the estimated position of goal on the horizontal plane while avoiding obstacles and using minimal computational power and memory (the boundary-following behavior uses an Artificial Potential Field to navigate around the obstacles). If the estimated goal position is reached but the salient-cue-sensor does not detect a salient quantity the higher level of the planner calls Dijkstra algorithm to computes the minimum-distance path to change the floor, assuming to know in advance the 2D position of the passages among different floors, and then moves vertically. The overall strategy is usefull for indoor inspection in hazardous scenarios. The algorithm is validated in simulation, investigating the robustness with respect to the laser-range-finder noise.

关键词： bug algorithms Minimal sensing Quadrotor Robot navigation Flying robots Hazardous scenarios Urban search and rescue

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Evolving EFSMs Solving a Path-Planning Problem by Genetic Programming 12

Evolving EFSMs Solving a Path-Planning Problem by Genetic Pr...

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14th International Conference on Genetic and Evolutionary Computation Conference (GECCO)

作者： Buzdalov, Maxim Sokolov, Andrey St Petersburg Natl Res Univ IT Mech & Opt 49 Kronverkskiy Prosp St Petersburg Russia

ISBN: (纸本)9781450311786

In this paper, we present an approach to evolving of an algorithm encoded as an extended finite-state machine that solves a simple path-planning problem - finding a path in an unknown area filled with obstacles using a constant amount of memory - by means of genetic programming. Experiments show that in 100% of cases a reasonably correct EFSM with behavior similar to one of the bug algorithms is evolved.

关键词： genetic programming path-planning problem bug algorithms finite-state machine

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Vizualizace hledání cesty pro robota

Vizualizace hledání cesty pro robota

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作者： Roubalík, Zbyněk Brno University of Technology

Tato práce se zabývá hledáním cesty robota za pomocí bug algoritmů a Potenciálových polí. Jsou zde popsány jednotlivé bug algoritmy, je zde vysvětlen princip Pot... 详细信息

Tato práce se zabývá hledáním cesty robota za pomocí bug algoritmů a Potenciálových polí. Jsou zde popsány jednotlivé bug algoritmy, je zde vysvětlen princip Potenciálových polí a způsob hledání cesty v těchto polích. Součástí této práce jsou také java applety sloužící pro demonstraci funkčnosti a principu těchto algoritmů, je zde uveden návrh i popis implementace a ovládání těchto appletů.

关键词： bug algoritmy bug1 bug2 Tangent bug Potenciálová pole Záplavové vyplňování Harmonická potenciálová pole robotika hledání cesty bug algorithms bug1 bug2 Tangent bug Potential fields Wave-front algorithm Harmonic potential field robotics pa

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