Car-like robot navigation at high speed

Rebai, Karima; Azouaoui, Ouahiba; Benmami, M.; Larabi, A.

doi:10.1109/robio.2007.4522484

Cited by 16 publications

(13 citation statements)

References 11 publications

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“…• heading: based on the final orientation of the robot regarding the goal position in the world; • dist: which prioritize movements over the areas free of obstacles (with the highest distance to collision); and • velocity: with focus on the desired linear velocity setpoint. Due to the nature of this optimization function, the DWA was adapted to several major goals [26], [27] and different robot types, like car-like robots [28], as well as to dynamic environments [24]. However, the robot and goal relative position to the world were known in these studies, which are susceptible to GPS localization problems.…”

Section: B Reactive Control: Idwamentioning

confidence: 99%

A Hybrid Controller for Vision-Based Navigation of Autonomous Vehicles in Urban Environments

Lima

Victorino

2016

IEEE Trans. Intell. Transport. Syst.

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International audienceThis paper presents a new hybrid control approach for vision-based navigation applied to autonomous robotic automobiles in urban environments. It is composed by a Visual Servoing (VS) for road lane following (as deliberative control) and a Dynamic Window Approach (DWA) for obstacle avoidance (as reactive control). Typically, VS applications do not change the velocities to stop the robot in dangerous situations or avoid obstacles while performing the navigation task. However, in several urban conditions, these are elements that must be dealt with to guarantee the safe movement of the car. As a solution for this problem, in this study a line following VS controller will be used to perform road lane following tasks with obstacle avoidance, validating its control outputs in a new Image-Based Dynamic Window Approach (IDWA). The final solution combines the benefits of both controllers (VS+IDWA) for optimal lane following and fast obstacle avoidance, taking into account the car kinematics and some dynamics constraints. Experiments in a challenging scenario with both simulated and real experimental car show the viability of the proposed methodology

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Section: B Reactive Control: Idwamentioning

confidence: 99%

A Hybrid Controller for Vision-Based Navigation of Autonomous Vehicles in Urban Environments

Lima

Victorino

2016

IEEE Trans. Intell. Transport. Syst.

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“…Other features to be taken into account are the shape and kinodynamic restrictions of the robot. For instance, Rebai, Azouaoui, Benmami, and Larabi (2007) adapts for carlike robots the well-known dynamic window approach (Fox, Burgard, & Thrun, 1997) used in differential drive robots. In Minguez and Montano (2009), the nearness diagram (Minguez & Montano, 2004) is adapted to meet the special shape and kinodynamic requirements of differential-drive robots.…”

Section: Related Workmentioning

confidence: 99%

Robust Navigation and Seamless Localization for Carlike Robots in Indoor-outdoor Environments

et al. 2016

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This paper describes a navigation and seamless localization system that permits carlike robots to move safely in heterogeneous scenarios within indoor and outdoor environments. The robot localization integrates different sensor (GPS, odometry, laser rangefinders) information depending on the kind of area (indoors, outdoors, and areas between) or on the sensor uncertainty in such a way that there are no discontinuities in the localization, and a bounded uncertainty is constantly maintained. Transitions through indoor and outdoor environments are thoroughly considered to assure a smooth change in‐between. The paper addresses a navigation technique that combines two well‐known obstacle avoidance techniques, namely the nearness diagram and the dynamic window approaches, exploiting the advantages and properties of both, and integrating the seamless localization technique. The navigation technique is developed for carlike robots by considering their shape and kinodynamic constraints, and the restrictions imposed by the environment. Forward‐backward maneuvers are also integrated in the method, allowing difficult situations in dense scenarios to be managed. The whole system has been tested in simulations and experiments in real large‐scale scenarios.

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“…The Dynamic Window Approach is a reactive obstacle avoidance technique proposed originally by [16], with a modification for car-like robots presented in [20], This approach optimize an objective function (2) in order to select the best control input regarding the desired configuration to the robot. The objective fonction is constituted with three weighted components: the goal position (heading), the obstacle distance (dist) and the final linear velocity (velocity), represented as:…”

Section: A Dynamic Window Approachmentioning

confidence: 99%

An approach of human driving behavior correction based on Dynamic Window Approach

Kang

Lima

Victorino

2014

2014 IEEE Intelligent Vehicles Symposium Proceedings

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This paper presents the approach of an applicable safety driving methodology for human drivers based on Dynamic Window Approach (DWA), as an implementation of Advanced Driving Assist Systems (ADASs). The human driving behaviors are modelled for the design of controller, refined by referential paths using evasive trajectory model, and the linear and angular velocities are limited and corrected by DWA which performed as an obstacle avoidance strategy. Results of trajectory following and obstacle avoidance are compared with the visual servoing (VS) controller as a corresponding approach of autonomous control pattern.

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Car-like robot navigation at high speed

Cited by 16 publications

References 11 publications

A Hybrid Controller for Vision-Based Navigation of Autonomous Vehicles in Urban Environments

A Hybrid Controller for Vision-Based Navigation of Autonomous Vehicles in Urban Environments

Robust Navigation and Seamless Localization for Carlike Robots in Indoor-outdoor Environments

An approach of human driving behavior correction based on Dynamic Window Approach

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