Reactive path planning in a dynamic environment
IEEE Transactions on Robotics
A new reactive target-tracking control with obstacle avoidance in a dynamic environment
ACC'09 Proceedings of the 2009 conference on American Control Conference
A reactive inverse PN algorithm for collision avoidance among multiple unmanned aerial vehicles
ACC'09 Proceedings of the 2009 conference on American Control Conference
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Real-time platooning of mobile robots: design and implementation
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Kinematics-based characterization of the collision course
International Journal of Robotics and Automation
Journal of Intelligent and Robotic Systems
Reinforcement based mobile robot navigation in dynamic environment
Robotics and Computer-Integrated Manufacturing
Adaptive human motion analysis and prediction
Pattern Recognition
Distributed reactive collision avoidance
Autonomous Robots
Pareto-optimal coordination of multiple robots with safety guarantees
Autonomous Robots
Guaranteeing motion safety for robots
Autonomous Robots
A novel obstacle avoidance algorithm: "Follow the Gap Method"
Robotics and Autonomous Systems
Multi Robot Collision Avoidance with Continuous Curvature Manoeuvres
Proceedings of Conference on Advances In Robotics
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A novel collision cone approach is proposed as an aid to collision detection and avoidance between irregularly shaped moving objects with unknown trajectories. It is shown that the collision cone can be effectively used to determine whether collision between a robot and an obstacle (both moving in a dynamic environment) is imminent. No restrictions are placed on the shapes of either the robot or the obstacle, i.e., they can both be of any arbitrary shape. The collision cone concept is developed in a phased manner starting from existing analytical results that enable prediction of collision between two moving point objects. These results are extended to predict collision between a point and a circular object, between a point and an irregularly shaped object, between two circular objects, and finally between two irregularly shaped objects. Using the collision cone approach, several strategies that the robot can follow in order to avoid collision, are presented. A discussion on how the shapes of the robot and obstacles can be approximated in order to reduce computational burden is also presented. A number of examples are given to illustrate both collision prediction and avoidance strategies of the robot