Theory and practice of reversing control on multiply-articulated vehicles

A path-tracking controller is presented for automating the reversing of multiply-articulated vehicles. This uses a state feedback approach and steers the wheels of the front axle to ensure that the rearmost vehicle unit tracks a specified path. Linear closed-loop analysis is performed and shows that the controller is stable for vehicles with up to six trailers. The controller is implemented on three full-size experimental heavy vehicles: a ‘tractor–semitrailer’, a ‘B-double’ vehicle and a ‘B-triple’ vehicle, which have one trailer, two trailers and three trailers respectively. Experimental results are presented and the controller performance is evaluated. All test vehicles were able to track the paths to within 400 mm of the desired path. This research was funded by the Engineering and Physical Sciences Research Council (EPSRC) and Volvo Trucks through an Industrial CASE award. The authors would like to acknowledge Leo Laine and Carl-Johan Hoel from Volvo Trucks for their collaboration and contributions to the research.This is the author accepted manuscript. The final version is available from Sage via http://dx.doi.org/10.1177/095440701559691

DEVELOPMENT OF TEST ENVIRONMENTS FOR REVERSE ASSIST FUNCTIONS AS APPLIED TO AN A-DOUBLE VEHICLE COMBINATION

High-capacity transport vehicles reduce costs and improve efficiency. Long vehicle combinations such as an A-double combination vehicle (Tractor + semitrailer + dolly + semitrailer) improve transportation efficiency but they are extremely difficult to manoeuvre in tight spaces and in the reverse direction. This document summarizes developing environments to test reverse assist functions as applied to the A-double combination vehicle. These environments create a rapid prototyping platform consisting of a virtual and a scaled environment to test and validate controller concepts. The behaviour of the plant model in the virtual environment, the scaled vehicle model and the plant model in VTM (Volvo Truck Model) are studied and compared. A proportional controller is developed to test the environments and evaluate the process of concept development using the rapid prototype platform. The controller performance is evaluated and a possibility of incorporating integral controller is discussed

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

Maneuvering a general 2-trailer with a car-like tractor in backward motion is a task that requires significant skill to master and is unarguably one of the most complicated tasks a truck driver has to perform. This paper presents a path planning and path-following control solution that can be used to automatically plan and execute difficult parking and obstacle avoidance maneuvers by combining backward and forward motion. A lattice-based path planning framework is developed in order to generate kinematically feasible and collision-free paths and a path-following controller is designed to stabilize the lateral and angular path-following error states during path execution. To estimate the vehicle state needed for control, a nonlinear observer is developed which only utilizes information from sensors that are mounted on the car-like tractor, making the system independent of additional trailer sensors. The proposed path planning and path-following control framework is implemented on a full-scale test vehicle and results from simulations and real-world experiments are presented.Comment: Preprin

Hybrid PSO-PWL-Dijkstra approach for path planning of non holonomic platforms in dense contexts

Planning is an essential capability for autonomous robots. Many applications impose a diversity of constraints and traversing costs in addition to the usually considered requirement of obstacle avoidance. In applications such as route planning, the use of dense properties is convenient as these describe the terrain and other aspects of the context of operation more rigorously and are usually the result of a concurrent mapping and learning process. Unfortunately, planning for a platform with more than three degrees of freedom can be computationally expensive, particularly if the application requires the platform to optimally deal with a thorough description of the terrain. The objective of this thesis is to develop and demonstrate an efficient path planning algorithm based on dynamic programming. The goal is to compute paths for ground vehicles with and without trailers, that minimise a specified cost-to-go while taking into account dynamic constraints of the vehicle and dense properties of the environment. The proposed approach utilises a Quadtree Piece-Wise Linear (QT-PWL) approximation to describe the environment in a low dimensional subspace and later uses a particle approach to introduce the dynamic constraints of the vehicle and to smooth the path in the full dimensional configuration space. This implies that the optimisation process can exploit the QT-PWL partition. Many usual contexts of operation of autonomous platforms have cluttered spaces and large regions where the dense properties are smooth; therefore, the QT-PWL partition is able to represent the context in a fraction of cells that would be needed by a homogeneous grid. The proposed methodology includes adaptations to both algorithms to achieve higher efficiency of the computational cost and optimality of the planned path. In order to demonstrate the capabilities of the algorithm, an idealized test case is presented and discussed. The case for a car and a tractor with multiple trailers is presented. A real path planning example is presented in addition to the synthetic experiments. Finally, the experiments and results are analysed and conclusions and directions for possible future work are presented

Locomotion system for ground mobile robots in uneven and unstructured environments

One of the technology domains with the greatest growth rates nowadays is service robots. The extensive use of ground mobile robots in environments that are unstructured or structured for humans is a promising challenge for the coming years, even though Automated Guided Vehicles (AGV) moving on flat and compact grounds are already commercially available and widely utilized to move components and products inside indoor industrial buildings. Agriculture, planetary exploration, military operations, demining, intervention in case of terrorist attacks, surveillance, and reconnaissance in hazardous conditions are important application domains. Due to the fact that it integrates the disciplines of locomotion, vision, cognition, and navigation, the design of a ground mobile robot is extremely interdisciplinary. In terms of mechanics, ground mobile robots, with the exception of those designed for particular surroundings and surfaces (such as slithering or sticky robots), can move on wheels (W), legs (L), tracks (T), or hybrids of these concepts (LW, LT, WT, LWT). In terms of maximum speed, obstacle crossing ability, step/stair climbing ability, slope climbing ability, walking capability on soft terrain, walking capability on uneven terrain, energy efficiency, mechanical complexity, control complexity, and technology readiness, a systematic comparison of these locomotion systems is provided in [1]. Based on the above-mentioned classification, in this thesis, we first introduce a small-scale hybrid locomotion robot for surveillance and inspection, WheTLHLoc, with two tracks, two revolving legs, two active wheels, and two passive omni wheels. The robot can move in several different ways, including using wheels on the flat, compact ground,[1] tracks on soft, yielding terrain, and a combination of tracks, legs, and wheels to navigate obstacles. In particular, static stability and non-slipping characteristics are considered while analyzing the process of climbing steps and stairs. The experimental test on the first prototype has proven the planned climbing maneuver’s efficacy and the WheTLHLoc robot's operational flexibility. Later we present another development of WheTLHLoc and introduce WheTLHLoc 2.0 with newly designed legs, enabling the robot to deal with bigger obstacles. Subsequently, a single-track bio-inspired ground mobile robot's conceptual and embodiment designs are presented. This robot is called SnakeTrack. It is designed for surveillance and inspection activities in unstructured environments with constrained areas. The vertebral column has two end modules and a variable number of vertebrae linked by compliant joints, and the surrounding track is its essential component. Four motors drive the robot: two control the track motion and two regulate the lateral flexion of the vertebral column for steering. The compliant joints enable limited passive torsion and retroflection of the vertebral column, which the robot can use to adapt to uneven terrain and increase traction. Eventually, the new version of SnakeTrack, called 'Porcospino', is introduced with the aim of allowing the robot to move in a wider variety of terrains. The novelty of this thesis lies in the development and presentation of three novel designs of small-scale mobile robots for surveillance and inspection in unstructured environments, and they employ hybrid locomotion systems that allow them to traverse a variety of terrains, including soft, yielding terrain and high obstacles. This thesis contributes to the field of mobile robotics by introducing new design concepts for hybrid locomotion systems that enable robots to navigate challenging environments. The robots presented in this thesis employ modular designs that allow their lengths to be adapted to suit specific tasks, and they are capable of restoring their correct position after falling over, making them highly adaptable and versatile. Furthermore, this thesis presents a detailed analysis of the robots' capabilities, including their step-climbing and motion planning abilities. In this thesis we also discuss possible refinements for the robots' designs to improve their performance and reliability. Overall, this thesis's contributions lie in the design and development of innovative mobile robots that address the challenges of surveillance and inspection in unstructured environments, and the analysis and evaluation of these robots' capabilities. The research presented in this thesis provides a foundation for further work in this field, and it may be of interest to researchers and practitioners in the areas of robotics, automation, and inspection. As a general note, the first robot, WheTLHLoc, is a hybrid locomotion robot capable of combining tracked locomotion on soft terrains, wheeled locomotion on flat and compact grounds, and high obstacle crossing capability. The second robot, SnakeTrack, is a small-size mono-track robot with a modular structure composed of a vertebral column and a single peripherical track revolving around it. The third robot, Porcospino, is an evolution of SnakeTrack and includes flexible spines on the track modules for improved traction on uneven but firm terrains, and refinements of the shape of the track guidance system. This thesis provides detailed descriptions of the design and prototyping of these robots and presents analytical and experimental results to verify their capabilities

Implementation of Reversing Control on a Doubly Articulated Vehicle

The problem of reversing vehicles with two trailers could be solved with a semi-autonomous assistance system for automatically steering the vehicle. In the literature found, no controllers have been implemented on a full-size vehicle with two trailers. In this paper, two simple path-tracking controllers are presented for automating the reversing of a “B-double” vehicle, consisting of a tractor and two trailers. One of the controllers is a heuristic “preview point” controller; the other uses a state feedback approach. The controllers steer the wheels on the front axle so as to stabilize the vehicle in reverse and control the path of the rearmost axle to follow a prescribed path. A tuning strategy is outlined where both controllers are tuned using the linear quadratic regulator and have the same closed-loop poles. The two controllers are implemented on a full-size B-double test vehicle. Experimental results are discussed, and the controller performances are evaluated against criteria. With the state feedback controller, the test vehicle was able to track target paths, consisting of a roundabout and a lane change, to within 50 mm.This research was funded by the Engineering and Physical Sciences Research Council (EPSRC) and Volvo Trucks through an Industrial CASE award. The authors would like to acknowledge Leo Laine and Carl-Johan Hoel from Volvo Trucks for their collaboration and contributions to the research. The authors would like to acknowledge Denby Transport for their loan of the ‘Extra’ Eco-Link B-trailer for use in vehicle testing. The authors would like to acknowledge the members of the CVDC who supported the work in this paper. At the time of writing, the Consortium consisted of the University of Cambridge with the following partners from the heavy vehicle industry: Anthony Best Dynamics, Camcon, Denby Transport, Firestone Air Springs, GOODYEAR DUNLOP, Haldex, Motor Industry Implementation of Reversing Control on a Doubly-Articulated Vehicle 15 Research Association, SDC Trailers, SIMPACK, Tinsley Bridge, Tridec, Volvo Trucks, and Wincanton