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The perception of the environment is one the most important tasks related to automated driving systems navigation. Typically, the robot detects the road surface and obstacles to perform the local navigation control safely. However, working with image data brings several problems related to environment elements like shadows, light reflection, low-variance textures, etc., which could compromise the...
Advanced Driver Assistance Systems (ADAS) are electronic systems, present on modern vehicles, which enhance the road safety by providing assistance on the driving act. These systems are usually associated with semi-autonomous and expensive vehicles. Oppositely, yet affordable, modern smartphones, endowed with an operating system, are capable of providing a high computational power allied to multiple...
This 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...
This paper presents a global behavioral architecture used as a coordinator for the global navigation of an autonomous vehicle in an urban context including traffic laws and other features. As an extension to our previous work, the approach presented here focuses on how this manager uses perceived information (from low cost cameras and laser scanners) combined with digital road-map data to take decisions...
This paper presents a sensor-based control strategy applied in the global navigation of autonomous vehicles in urban environments. Typically, sensor-based control performs local navigation tasks regarding some features perceived from the environment. However, when there is more than one possibility to go, like in road intersection, the vehicle control fails to accomplish its global navigation. In...
This paper presents an approach for the development of Advanced Driving Assistance System (ADAS) based on the human-vehicle interaction using Image-based Dynamic Window Approach (IDWA). The IDWA is associated to a method for dynamic obstacles avoidance in order to prevent human driving errors, in the context of intelligent robotic vehicles. The human-vehicle interaction is presented by the correction...
This paper presents a local navigation strategy with obstacle avoidance applied to autonomous robotic automobiles in urban environments, based on the validation of a Visual Servoing controller in a Dynamic Window Approach. Typically, Visual Servoing applications do not consider velocity changes to stop the robot in danger situations or avoid obstacles, while performing the navigation task. However,...
This paper presents the approach of an applicable safety driving methodology for human drivers with focus on human-vehicle interaction. The approach is based on Dynamic Window Approach (DWA) in co-operation with perception of the obstacles. The human driving behaviors are modelled for the design of controller, refined by referential paths using evasive trajectory model, where linear and angular velocities...
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...
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