This paper describes the dynamic window approach to reactive collision avoidance for mobile robots equipped with synchro-drives. The approach is derived directly from the motion dynamics of the robot and is therefore particularly well-suited for robots operating at high speed. It differs from

The dynamic window approach is a well known navigation scheme developed by Fox et. al. [1] and extended by Brock and Khatib [2]. 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

The dynamic window approach is a well known navigation scheme developed in Fox et al. (1997) and extended in Brock and Khatib (1999). It is safe by construction and has been shown to perform very e#ciently in experimental setups. However, one can construct examples where the proposed scheme

This paper describes the dynamic windowapproachto reactive collision avoidance for mobile robots equipped with synchro-drives. The approach isderived directly from the motion dynamics of the robot and istherefore particularly well-suited for robotsoperatingat high speed. It di ers from previous

In this paper we present an anticipative local navigation algorithm for an autonomous mobile robot. The purpose of local navigation is to move the robot according to a specified goal, like a planned path to a target, and avoiding collisions with obstacles during operation. The robot is perceiving its immediate surroundings by laser and sonar range scanners and by a stereo camera. All the sensor information is represented in a local map. In order to chose the best action, a number of possible trajectories are then evaluated. The trajectories are modelled as clothoid curves, a parametric curve which is well suited for moving vehicles. A fitness function that takes into account the likelihood of collisions, the compliance with the navigation goal and the speed that can be achieved selects the best trajectory, which is then translated into motion commands for the drive system. 1

declaration. A novel algorithm for odor path likelihood mapping in the dynamic airflow environment is proposed. The algorithm has a low computation cost by importing the idea of dynamic window approach. Experiments are carried out on the mobile robot in which odor concentration sensor, airflow sensor, encoder

This work presents a safe navigation approach for a car-like robot. The approach relies on a global motion plan-ning based on Velocity Vector Fields along with a Dy-namic Window Approach for avoiding unmodeled ob-stacles. Basically, the vector field is associated with a kinematic, feedback

is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has

Abstract — This paper presents an extension of current Global Dynamic Window approaches to arbitrarily shaped holonomic and non-holonomic mobile robots. The algorithm proceeds in two stages. In order to account for an arbitrary robot cross section, the first stage takes the robot’s orientation

Abstract—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