Nonholonomic mobile robot formation control with kinodynamic constraints
PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots
International Journal of Robotics Research
A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance
Journal of Intelligent and Robotic Systems
A Novel Time Decaying Approach to Obstacle Avoidance
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
A new reactive target-tracking control with obstacle avoidance in a dynamic environment
ACC'09 Proceedings of the 2009 conference on American Control Conference
Prioritized sensor detection via dynamic Voronoi-based navigation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Sound source tracking and obstacle avoidance for a mobile robot
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Development of a navigation system for heterogeneous mobile robots
International Journal of Intelligent Systems Technologies and Applications
Prioritized Sensor Detection for Environmental Mapping: Theory and Experiments
Journal of Intelligent and Robotic Systems
Planning and obstacle avoidance in mobile robotics
Robotics and Autonomous Systems
Collision free cooperative navigation of multiple wheeled robots in unknown cluttered environments
Robotics and Autonomous Systems
A Method of Boundary Following by a Wheeled Mobile Robot Based on Sampled Range Information
Journal of Intelligent and Robotic Systems
Integrated Obstacle Avoidance and Path Following Through a Feedback Control Law
Journal of Intelligent and Robotic Systems
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The dynamic window approach (DWA) is a well-known navigation scheme developed by Fox et al. and extended by Brock and Khatib. It is safe by construction, and has been shown to perform very efficiently in experimental setups. However, one can construct examples where the proposed scheme fails to attain the goal configuration. What has been lacking is a theoretical treatment of the algorithm's convergence properties. Here we present such a treatment by merging the ideas of the DWA with the convergent, but less performance-oriented, scheme suggested by Rimon and Koditschek. Viewing the DWA as a model predictive control (MPC) method and using the control Lyapunov function (CLF) framework of Rimon and Koditschek, we draw inspiration from an MPC/CLF framework put forth by Primbs to propose a version of the DWA that is tractable and convergent.