Vector Field Histogram Research Articles

The active kinematic histogram method for path planning of non-point, non-holonomically constrainted mobile robots

The paper presents a novel path planning method for non-point, non-holonomically constrainted mobile robots. The proposed method, named the Active Kinematic Histogram (AKH) method, is a potential field path-planning method based on the Vector Field Histogram (VFH) method introduced by J. Borenstein and Y. Koren. The method relies on one-dimensional environment representations named AKHs, derived from the available information on the obstacle space and the robot itself. The AKHs provide the information abstraction required for fast, collision-free and kinematically feasible path planning for non-point, non-holonomically constrainted mobile robots. The method constructs two AKH structures incorporating the information stored in occupancy grid environment representations as well as the exact robot's size, shape and kinematic features. The method applies simple and fast procedures, e.g. histogram shifting, in order to determine kinematic feasibility and the result of the robot's steering limits. Being a potential field method, the AKH method uses adaptive thresholding procedures to reduce the inherited drawback of the local minima traps phenomenon. Furthermore, the method proposes specific updating and coding procedures for the environmental information and introduces the Ageing function to insert time parameterization in the path-planning results. Also, the so-called bicycle kinematic model is presented in order to describe the kinematic family of mobile robots suitable for applying the AKH method. The method integrates a velocity control procedure which is also based on information provided by the active kinematic histograms. The method produced smooth, collision-free paths in a variety of experimental configurations. Simulation and experimental results are presented.

The vector field histogram-fast obstacle avoidance for mobile robots

A real-time obstacle avoidance method for mobile robots which has been developed and implemented is described. This method, named the vector field histogram (VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target. The VFH method uses a two-dimensional Cartesian histogram grid as a world model. This world model is updated continuously with range data sampled by onboard range sensors. The VFH method subsequently uses a two-stage data-reduction process to compute the desired control commands for the vehicle. Experimental results from a mobile robot traversing densely cluttered obstacle courses in smooth and continuous motion and at an average speed of 0.6-0.7 m/s are shown. A comparison of the VFN method to earlier methods is given.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>