A statistical approach for uncertain stability analysis of mobile robots

Abstract

Abstract-Stability prediction is an important concern for mobile robots operating in rough environments. Having the capacity to predict areas of instability means pro-actively being able to plan safer traversable paths. The most influential tip-over stability measures are based on two criteria, the robot's center of mass (CM) and the supporting polygon (SP) defined by the convex area spanned between the ground contact-points. However, there is significant uncertainty associated with many parameters in the planning pipe-line: the actual robot kino-dynamic model, its localisation in the ground, and the terrain models, particularly in uneven terrain. This article proposes a statistical analysis of stability prediction to account for some of the uncertainties. This is accomplished using the force angle (FA) stability measure for a reconfigurable multi-tracked vehicle fitted with flippers, a manipulator arm and a sensor head. Probability density function (PDF) of contact-points, CM and the FA stability measure are numerically estimated, with simulation results performed on the open dynamics engine (ODE) simulator based on uncertain parameters. Two techniques are presented: a conventional Monte Carlo scheme, and a structured unscented transform (UT) which results in significant improvement in computational efficiency. Experimental results on maps obtained from a range camera fitted on the sensor head while the robot traverses over a ramp and a series of steps are presented that confirms the validity of the proposed probabilistic stability prediction method.

Path planning for a tracked robot traversing uneven terrains based on tip‐over stability

“…It can meet the maximum climbing limit of the robot. According to the evaluation function (20), path 2 has the lowest cost and can be used as the final optimal path.…”

“…The open dynamic engine (ODE [19]) has been widely used in attitude estimation. Norouzi et al [20] used the ODE to estimate the uncertain height, roll, and pitch angle of the robot to estimate the stability measure, with the purpose to use the A‐star algorithm. The work by Fabian et al [21] presents a novel iterative geometric method that reduces the problem of robot attitude prediction to a two‐dimensional image‐processing operations by introducing the concept of robot heightmap.…”

A Multi-modal Utility to Assist Powered Mobility Device Navigation Tasks

“…Outdoor applications must also take into account obstacles identified by PMD users to be difficult to pass [18] such as groups of people. Downward-pitched stereo cameras or an IR depth imager could be used to provide height-maps and additional stability/traversability information [19,20] for planning algorithms; a study left for future development and investigation. This paper describes several solutions to assist caregiver staff by reducing the need to monitor PMD users in everyday mobility tasks related to patient care.…”

Pose estimation-based path planning for a tracked mobile robot traversing uneven terrains

“…Recently, Beck et al proposed that the robot's tip-over stability measure can be used to plan safer traversable paths for tracked mobile robots [10], and Norouzi et al used a dynamic simulator (ODE [11]) to estimate the robot's uncertain height, roll and pitch values in order to estimate this stability measure, with the purpose to search the path that optimizes the stability using the A * algorithm [12]. The tip-over stability is computed as proposed by Papadopoulos and Rey [13] (a.k.a.…”