Potential Field Navigation of High Speed Unmanned Ground Vehicles on Uneven Terrain

Abstract

Abstract-This paper proposes a potential field-based method for high speed navigation of unmanned ground vehicles (UGVs) on uneven terrain. A potential field is generated in the two-dimensional "trajectory space" of the UGV path curvature and longitudinal velocity. Dynamic constraints, terrain conditions, and navigation conditions can be expressed in this space. A maneuver is chosen within a set of performance bounds, based on the potential field gradient. In contrast to traditional potential field methods, the proposed method is subject to local maximum problems, rather than local minimum. It is shown that a simple randomization technique can be employed to address this problem. Simulation and experimental results show that the proposed method can successfully navigate a UGV between pre-defined waypoints at high speed, while avoiding unknown hazards. Further, vehicle velocity and curvature are controlled to avoid rollover and excessive side slip. The method is computationally efficient, and thus suitable for on-board real-time implementation.

Exponential Fields Formulation for WMR Navigation

“…The term F o t is the robot's internal motivation with functional form in (17), which makes the robot move along multiple local goals. Where δ = x t+1 − x t is the distance between the actual robot location x t and the next desired goal x t+1 .…”

“…Shimoda et al [17] proposed a potential fieldbased method for high speed navigation of unmanned ground vehicles on uneven terrain, where local minima and maxima problems were addressed with a simple randomization technique. Kareem et al [18] presented a fuzzy potential field approach for mobile robot motion planning using two fuzzy models for each field, repulsive and attractive respectively.…”

Egocentric affordance fields in pedestrian steering

“…The A* algorithm and its derivatives [Hart et al 1968;Hart et al 1972;Dechter and Pearl 1985;Trovato and Dorst 2002] tend to produce non-realistic routes and require smoothing techniques in addition to a steering mechanism for dynamic collision avoidance. The approach of potential fields [Warren 1989;Warren 1990;Shimoda et al 2005] generates a global field for the entire landscape where the potential gradient is contingent upon the presence of obstacles and distance to goal. Since a change in target or environment requires significant re-computation, these navigation methods are generally confined to systems with non-changing goals and static environments.…”

“…They are often tackled as separate problems that need to be interfaced for a fully functional navigation system. Approaches such as A* [Hart et al 1968] and potential fields [Warren 1990;Shimoda et al 2005] are popular planning methods for pedestrian simulations. Given a target location and an obstacle laden environment, these techniques compute a global path to the target.…”

“…Field-based approaches (e.g. [Shimoda et al 2005]) effectively compute plans on the required scale, but do not take into account time and require storing large high-resolution fields for the entire environment.…”