Fast Traction Control of Rovers on Prescribed Dynamic Trajectories with
Wheel-Fighting Consideration
Abstract
To reliably localize and control wheeled autonomous rovers, their
controllers must keep the wheels away from traction loss. In this paper,
we develop a fast and practical traction control system for rovers that
track dynamic trajectories on rough firm terrains, leveraging their
normally existing redundant control directions. Trajectory-tracking
performance is guaranteed by input-output linearizing a nonholonomic
model of the system and employing an appropriate stabilizing control
law. We propose a novel methodology to optimally lift the control
signals at the rover’s output level to determine the control actions
that enhance the system’s traction without affecting the tracking
performance. The methodology uses the knowledge of wheels’ friction
coefficients and estimation of normal and tractive forces based on a
nonholonomic rover model to optimally distribute the tractive forces
among the wheels. The novelty is in redefining the optimization problem
in both lateral and longitudinal directions that require minimum
information about wheel-ground interactions and leads to linear
optimality conditions. We define the notion of total required
force/moment at system’s center of mass to (i) introduce reference
directions for tractive forces in the proposed cost functions, and (ii)
identify the rover wheels fighting against the motion. To prevent
wheel-fighting, we find sub-optimal solutions that suppress tractive
forces at the fighting wheels. The proposed traction control system is
implemented on a six-wheel autonomous Lunar rover and its efficacy is
investigated by a developed software-in-the-loop simulation environment
using Vortex Studio. This software simulates a 3-dimensional digital
twin of the system, with different terrain and tire model options. When
compared to the conventional pseudo-inverse solution, the developed
traction controller demonstrates improved overall traction and it saves
the rover from traction loss.