Navigation of an Autonomous Car Using Vector Fields and the Dynamic Window Approach

Lima, Danilo Alves de; Pereira, Guilherme A. S.

doi:10.1007/s40313-013-0006-5

Cited by 36 publications

(22 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Actualized with the robot movement, the occupancy grid contains only the local obstacles around the robot. For more details about the obstacle detection and occupancy grid layers, see [14]. This implementation considers only static environments for validation purposes, which does not restrain a future implementation with dynamic environments as presented in [15].…”

Section: General Definitionsmentioning

confidence: 99%

Autonomous vehicle global navigation approach associating sensor based control and digital maps

Pereira

Lima

Victorino

2014

2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014)

View full text Add to dashboard Cite

This paper proposes a global navigation strategy for autonomous vehicle combining sensor based control and digital maps information. In order to avoid localization problems in urban environments, this approach intends to solve the global navigation focusing on two local navigation tasks: road lane following and road intersection maneuvers. For that, it is important to use digital maps, once they provide a rich database containing information about the environment structure, like speed limit, number of lanes, traffic directions, etc. Associating the data extracted from the digital map with local navigation approaches, the vehicle is able to perform its global navigation task. The experiments take into account real data and a simulated scenario, which show the viability of this approach.

show abstract

Section: General Definitionsmentioning

confidence: 99%

Autonomous vehicle global navigation approach associating sensor based control and digital maps

Pereira

Lima

Victorino

2014

2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014)

View full text Add to dashboard Cite

show abstract

“…The obstacle avoidance methodology must validate the VS control input or choose an alternative which will result in less VS error. In this context, in [22] was presented a method for car-like robot navigation based on the validation of a Velocity Vector Field in a Dynamic Window Approach (DWA) [6]. This hybrid controller follows the vector field when it is valid, and it avoids obstacles prioritizing the final orientation of the vector field.…”

Section: Introductionmentioning

confidence: 99%

“…To do so, the VS equations were integrated in the DWA, compounding a new IDWA 1 [5]. This combination results in a hybrid controller (VS+IDWA) regardless the vehicle localization, diverging from the methodology presented in [22], which required a global path planning and a localization system. This work also diverges from the previous ones [15], [19], [20] based on VS, because the obstacle avoidance proposed with the DWA incorporates in an intrinsic way path following and velocity control behavior in its calculation, without changing the control law.…”

Section: Introductionmentioning

confidence: 99%

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

Lima

Victorino

2016

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

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

show abstract

“…Commands such as throttle, brake, steering, and gear shifting have been automated and controlled by a computer through a real-time network. Several developments have been made in this project, which allowed the car to drive itself in scenarios with obstacles using cameras and other sensors [1]. In this paper, we present the longitudinal velocity controller of this vehicle.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal Model Identification and Velocity Control of an Autonomous Car

Dias

Pereira

Palhares

2014

IEEE Trans. Intell. Transport. Syst.

Self Cite

View full text Add to dashboard Cite

This paper presents the model identification and the velocity control of an autonomous car. The control system was designed so that the car is controlled at low speeds, where the main applications for the vehicle's autonomous operations include parking and urban adaptive cruise control. A longitudinal model of the car was used in the control loop to compensate the nonlinear behavior of its dynamics. Since the determination of the vehicle's model is a difficult step in the design of model-based controllers, the main contribution of this paper is the use of an empirically determined model to this end. In this paper, the structure of the model was conceived from the car's physics equations, but its parameters were estimated using data-based identification techniques. An important contribution of this paper is the fact that, although the model is strictly linear, we can change its parameters as a function of the operation point of the vehicle to represent the engine's and the transmission's nonlinear behaviors. Moreover, in this paper, we propose a way to include changes in the longitudinal dynamics caused by the automatic gear shifting. The validation of the proposed controller was conducted by computer simulations and real-world experiments.

show abstract

Navigation of an Autonomous Car Using Vector Fields and the Dynamic Window Approach

Cited by 36 publications

References 23 publications

Autonomous vehicle global navigation approach associating sensor based control and digital maps

Autonomous vehicle global navigation approach associating sensor based control and digital maps

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

Longitudinal Model Identification and Velocity Control of an Autonomous Car

Contact Info

Product

Resources

About