Motion planning for a reversing general 2-trailer configuration using Closed-Loop RRT

Abstract

Abstract-Reversing with a dolly steered trailer configuration is a hard task for any driver without extensive training. In this work we present a motion planning and control framework that can be used to automatically plan and execute complicated manoeuvres. The unstable dynamics of the reversing general 2-trailer configuration with off-axle hitching is first stabilised by an LQ-controller and then a pure pursuit path tracker is used on a higher level giving a cascaded controller that can track piecewise linear reference paths. This controller together with a kinematic model of the trailer configuration is then used for forward simulations within a Closed-Loop Rapidly Exploring Random Tree framework to generate motion plans that are not only kinematically feasible but also include the limitations of the controller's tracking performance when reversing. The approach is evaluated over a series of Monte Carlo simulations on three different scenarios and impressive success rates are achieved. Finally the approach is successfully tested on a small scale test platform where the motion plan is calculated and then sent to the platform for execution.

A path planning and path‐following control framework for a general 2‐trailer with a car‐like tractor

“…To generate the figure‐eight nominal path in forward motion, a list of waypoints of the same shape was first constructed manually. The nominal path was generated by simulating the model of the G2T with a car‐like tractor (1) in forward motion with m/s, together with the pure pursuit controller in Evestedt et al (). The path taken by the vehicle , was then stored and used as the nominal path in forward motion.…”

“…A drawback with motion planning algorithms that rely on input‐space discretization, is that they lack completeness and optimality guarantees. Moreover, input‐space discretization is, in general, not applicable for unstable systems, unless the online simulations are performed in closed‐loop with a stabilizing feedback controller (Evestedt et al, ).…”

On Motion Planning Using Numerical Optimal Control

“…In [42], rrt is instead used to sample the input to a closed-loop system with an underlying controller (cl-rrt), i.e., a controller is acting as the steering function which removes the need of using an ocp solver online. Furthermore, the cl-rrt algorithm can reliably be applied to unstable systems, where the controller is used to stabilize the system [26]. On the downside, no optimization of the search tree by rewiring (as used in rrt * ) can be performed with cl-rrt since states cannot be connected exactly with this choice of inexact steering function.…”

Lattice-based motion planning for a general 2-trailer system

“…To include the general 2-trailer system within a motion planning framework, we presented a probabalistic sampling based approach in [8]. Even though the planner was capable of solving several complicated problems, the framework lacks any guarantees for completeness and optimality.…”