A hybrid feedback controller for car-like robots – combining reactive obstacle avoidance and global replanning

Hentschel, Matthias; Wulf, Oliver; Wagner, Bernd

doi:10.3233/ica-2007-14102

Cited by 11 publications

(8 citation statements)

References 13 publications

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“…Following the preplanned path is achieved by a hybrid feedback controller introduced in [2]. This controller enables precise path tracking as well as obstacle avoidance.…”

Section: Path Followingmentioning

confidence: 99%

Autonomous robot navigation based on OpenStreetMap geodata

Hentschel

Wagner

2010

13th International IEEE Conference on Intelligent Transportation Systems

Self Cite

101

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This paper introduces the appliance of standardized, free to use and globally available geodata for autonomous robot navigation. For this, data from the famous collaborative OpenStreetMap (OSM) mapping project are used. These geodata are public domain and include rich information about streets, tracks, railways, waterways, points of interest, land use, building information and much more. Beyond the spatial information, the geodata contain detailed information about the name, type and width of the streets as well as public speed limits. As a contribution of this paper, the OSM data are integrated for the first time into the robot tasks of localization, path planning and autonomous vehicle control. Following the description of the approach, experimental results in outdoor environments demonstrate the effectiveness of this approach.

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“…Following the preplanned path is achieved by a hybrid feedback controller introduced in [2]. This controller enables precise path tracking as well as obstacle avoidance.…”

Section: Path Followingmentioning

confidence: 99%

Autonomous robot navigation based on OpenStreetMap geodata

Hentschel

Wagner

2010

13th International IEEE Conference on Intelligent Transportation Systems

Self Cite

101

View full text Add to dashboard Cite

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“…Following the preplanned path P is achieved by a hybrid feedback controller introduced by Hentschel et al in [18]. This controller enables precise tracking of the planned path as well as obstacle avoidance.…”

Section: Vehicle Controlmentioning

confidence: 99%

An Adaptive Memory Model for Long-Term Navigation of Autonomous Mobile Robots

Hentschel

Wagner

2011

Journal of Robotics

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This paper introduces an environmental representation for autonomous mobile robots that continuously adapts over time. The presented approach is inspired by human memory information processing and stores the current as well as past knowledge of the environment. In this paper, the memory model is applied to time-variant information about obstacles and driveable routes in the workspace of the autonomous robot and used for solving the navigation cycle of the robot. This includes localization and path planning as well as vehicle control. The presented approach is evaluated in a real-world experiment within changing indoor environment. The results show that the environmental representation is stable, improves its quality over time, and adapts to changes.

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“…A set of both simulation and experimentation tests were developed with k u = k ω = 1 in (19). During these evaluations, it can be noticed that the mobile robot follows the desired trajectory, but in an oscillatory way (Rosales, et al 2009).…”

Section: Remarkmentioning

confidence: 99%

“…Das et al 9 designed an input-output feedback linearization controller and used a switching strategy to control formations, although there is a constraint that the leader velocity is bounded away from zero. In the second case, algorithms used to avoid obstacles replan the trajectory in order to avoid a collision; 19 then, a new reference trajectory, which must be followed by the robot, is generated. In the present work these values are called formation states.…”

Section: Introductionmentioning

confidence: 99%

Formation control and trajectory tracking of mobile robotic systems – a Linear Algebra approach

et al. 2010

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A novel approach for trajectory tracking of a mobile-robots formation by using linear algebra theory and numerical methods is presented in this paper. The formation controller design is based on the formation states concept and the dynamic model of a unicycle-like nonholonomic mobile robot. The proposed control law designed is decentralized and scalable. Simulations and experimental results confirm the feasibility and the effectiveness of the proposed controller and the advantages of using the dynamic model of the mobile robot. By using this new strategy, the formation of mobile robots is able to change its configuration (shape and size) and follow different trajectories in a precise way, minimizing the tracking and formation errors.

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A hybrid feedback controller for car-like robots – combining reactive obstacle avoidance and global replanning

Cited by 11 publications

References 13 publications

Autonomous robot navigation based on OpenStreetMap geodata

Autonomous robot navigation based on OpenStreetMap geodata

An Adaptive Memory Model for Long-Term Navigation of Autonomous Mobile Robots

Formation control and trajectory tracking of mobile robotic systems – a Linear Algebra approach

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