Proceedings ArticleDOI
A controller to perform a visually guided tracking task in a cluttered environment
Viviane Cadenat,R. Swain,P. Soueres,M. Devy +3 more
- Vol. 2, pp 775-780
Reads0
Chats0
TLDR
The proposed method combines visual servoing techniques allowing the target to be tracked, with an obstacle avoidance strategy based on the information provided by a 2D laser range sensor to drive a mobile robot towards a target in a cluttered environment.Abstract:
Presents a controller for driving a mobile robot towards a target in a cluttered environment The proposed method combines visual servoing techniques allowing the target to be tracked, with an obstacle avoidance strategy based on the information provided by a 2D laser range sensor Simulation results are presented at the end of the paperread more
Citations
More filters
Journal ArticleDOI
A redundancy-based iterative approach for avoiding joint limits: application to visual servoing
François Chaumette,Eric Marchand +1 more
TL;DR: This work first recalls the classical gradient projection approach and then presents a far more efficient method that relies on the iterative computation of motion that does not affect the task achievement and ensures the avoidance problem.
Journal ArticleDOI
Wheeled Mobile Robots: A review
Ramón Silva Ortigoza,Mariana Marcelino Aranda,Gilberto Silva Ortigoza,Victor Manuel Hernandez Guzman,M. A. M. Vilchis,G. S. Gonzalez,Juan Carlos Herrera Lozada,M. O. Carbajal +7 more
TL;DR: A literature review on wheeled mobile robots points out the main considerations to be taken into account when designing this class of robots and summarizes the most important approaches to render mobile robots autonomous.
Journal ArticleDOI
A Hybrid Controller for Vision-Based Navigation of Autonomous Vehicles in Urban Environments
TL;DR: 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.
Proceedings ArticleDOI
A controller to avoid both occlusions and obstacles during a vision-based navigation task in a cluttered environment
David Folio,V. Cadenat +1 more
TL;DR: A sensor-based controller allowing to visually drive a mobile robot towards a target while avoiding visual features occlusions and obstacle collisions is presented.
Proceedings ArticleDOI
Mixed camera-laser based control for mobile robot navigation
D. Dedieu,V. Cadenat,P. Soueres +2 more
TL;DR: Two control strategies based on the data provided by a camera and a 2D laser range sensor for driving a mobile robot towards a target amidst obstacles are presented.
References
More filters
Journal ArticleDOI
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Book
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
Book ChapterDOI
A new approach to visual servoing in robotics
TL;DR: Vision-based control in robotics based on considering a vision system as a specific sensor dedicated to a task and included in a control servo loop is described, and stability and robustness questions arise.
Book
Robot Control: The Task Function Approach
TL;DR: From the Publisher: A complete approach to the problem of controlling robot manipulators needs to bring together three scientific branches: computer science, mechanics, and automatic control.
Journal ArticleDOI
Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing
TL;DR: In this method, the self-localization of the robot is achieved by a model-based vision system, and nonstop navigation is realized by a retroactive position correction system.