**1. Introduction**

Vehicle FURBOT (Freight Urban RoBOTic vehicle) is a complete drive-by-wire electric freight vehicle designed to operate in last-mile delivery operations in an urban environment. The vehicle was part of the European Green Vehicles Initiative (EGVI) funded under the umbrella of the FP7-Transport European project ending in December 2015 [1,2]. The vehicle was completed as an entire drive-by-wire vehicle with the possibility of being upgraded to an autonomous vehicle. Currently, the project is being developed to convert it from a drive-by-wire to a completely autonomous vehicle. Thus, the necessity of autonomous freight collection is generated.

For autonomous vehicle navigation, a mathematical model has been built for performance evaluation of the vehicle [3] which is later used for developing sensor-based strategies for obstacle avoidance [4]. Further automation is achieved by controlling the pallet handling robot using hydraulic pressure-flow rate control [5]. Strategies are built to convert the vehicle from drive-by-wire to a completely autonomous vehicle [6]. Additionally, work on perception and control strategies for autonomous docking of the freight has also been previously studied [7]. This work is the next step in attaining the automation of the vehicle for it to auto-load its freight.

FURBOT has to take part in SHOW (SHared automation Operating models for Worldwide adoption) project where it is required to deliver freight autonomously to customers across an urban area. Currently, the vehicle is not equipped with proper algorithms for the autonomous collection of freight. However, the vehicle will be equipped with autonomous navigation software, which has its own autonomous parking algorithms [8,9]. The autonomous freight collection requires the vehicle to park next to the freight, such that it can collect freight autonomously. For that, a need for generation of correct parking pose

**Citation:** Masood, K.; Morales, D.P.; Fremont, V.; Zoppi, M.; Molfino, R. Parking Pose Generation for Autonomous Freight Collection by Pallet Handling Car-like Robot. *Energies* **2021**, *14*, 4677. https:// doi.org/10.3390/en14154677

Academic Editor: Guzek Marek

Received: 5 July 2021 Accepted: 30 July 2021 Published: 1 August 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

is required so the already available parking algorithms can maneuver the vehicle to the correct parking pose. Thus, the need for our work.

The role of autonomous vehicles in an urban environment is still being studied, and there is a gap in understanding the role of urban autonomous vehicles in smart urban mobility [10]. Autonomous freight delivery and their adoption in society are in preliminary stages, and surveys are being conducted for their acceptability in the society [11]. Further studies are being conducted to understand the role of autonomous vehicles in logistics [12]. Still, the concept of using manned deliveries for last-mile delivery through autonomous vehicles is being studied [13]. Privately-owned autonomous vehicles not designed for freight delivery are being looked into, and their potential is being discussed [14]. Currently, autonomous freight delivery through a designated autonomous freight vehicle is still a new subject, and the latest research proves that the solution for autonomous freight delivery is yet to be explored.

Freight delivery in an urban environment comes with many predefined constraints, e.g., loading constraints, vehicle routing problems [15] or compartment and order fulfillment related issues [16]. Many types of loading constraints and vehicle routing problems are discussed in [15,17]. Vehicle compartment issues are further divided into the flexibility of compartment sizes, assignment of product types, and share-ability of compartments. In contrast, order fulfillment issues comprise the mode of demand fulfillment and the total number of visits per customer [16]. However, all these logistic issues do not deal with how the freight needs to be loaded in the vehicle, especially dealing with the freight loading autonomously.

The generation of a parking spot for autonomous vehicles has also been studied in-depth in the last decade. Many next-generation vehicles are already equipped with autonomous parking [18]. New research in parking solutions varies in finding niche problems within the vehicle parking solution domain, including vision-based indoor parking [19], parking of fleet of vehicles [20], collision-avoidance-based parking [21] and sensor (Lidar) based parking solutions [22]. However, it is challenging to find parking solutions for freight vehicles, especially for freight loading. The closest work on autonomous parking for articulate vehicles is studied in [23], but it is still insufficient in resolving freight-based parking solutions. As FURBOT is a designated freight handling vehicle, the parking solution for autonomous loading of freight needs to be resolved.

Path generation and detecting correct parking pose for the vehicle are interesting subjects, especially in autonomous vehicles as they need to park by themselves. Usual work on vehicle parking pose estimation comes from parking pose marking recognition [24] or using a camera to detect these markings [25]. Apart from parking pose recognition from sensor feedback, estimation of parking pose requires solving geometrical equations for path generation or calculating current parking pose [26,27]. This research also exploits geometrical equations after freight detection to generate a parking pose that can solve the autonomous freight collection problem.

Electric freight vehicle poses a unique challenge for the creation of parking pose concerning freight for its collection. As it is not possible to make the freight perfectly align with any known orientation before loading the freight. Furthermore, there is a hassle for aligning freight to an orientation each time before loading the freight, even if a solution exists. It is much easier to consider autonomously loading the freight through aligning the vehicle w.r.t the freight. However, previous research in this domain is not available, i.e., the generation of parking pose for a freight handling vehicle for freight collection. Furthermore, the vehicle FURBOT is unique because it loads the freight sideways within itself through its loading bays, unlike typical forklift trucks.

This research is a step towards an autonomous collection of freight for the vehicle, especially the part of creating autonomous parking pose w.r.t freight keeping in line the constraints posed by vehicle FURBOT. Currently, there is no alternative solution for collecting freight autonomously for such vehicles. The ability to create a parking pose w.r.t an inanimate object, which is subject to change its orientation and position, is not

previously studied and discussed, thus the need of this research. The highlight of this research is creating a parking pose for such a vehicle, keeping in mind the constraints posed by the freight and the vehicle. Finally, testing the results to validate the proposed mathematical modeling for the solution to the unique problem.

In the next section, we discuss the problem and approach to the parallel freight parking issue, discussing the issues concerning freight detection, how the vehicle should be oriented for collection of the freight, and how parking spot should be defined w.r.t freight. Following, in Section 3, the software and control architecture of the vehicle is discussed, focusing on desired parking pose for the collection of freight. In Section 4, a mathematical model for vehicle parking pose is discussed. This section also covers the vehicle kinematic model and mathematical equations and notations for creating the parking pose for each loading bay of the vehicle. Section 5 elaborates on the desired results achieved of the parking pose for each loading bay of the vehicle, and the results are further verified for different freight poses, and the parking pose is validated as per requirement. Finally, in Section 6, the conclusions of the research are discussed.

### **2. Problem and Approach**

The considered vehicle has to park, keeping the freight on the vehicle's right-hand side for loading the freight through the designed loading bays. There are three core steps in defining the parking spot for the vehicle for the autonomous collection of freight. The critical issues in defining the parking spot are freight detection, the vehicle's orientation, and defining parking spot reference to freight. These issues are further elaborated in their sub-sections below.

#### *2.1. Freight Detection*

The first step in defining the parking spot for the vehicle for loading freight autonomously is the detection of freight location. The freight vehicle is equipped with 3D LIDAR, which can identify and distinguish freight from the environment as the freight has a unique shape, size and color from the usual environment. Image feedback from an on-board camera is also used to distinguish freight from the environment. The design and dimensions of the vehicle freight box are given in Figure 1 (dimensions in mm), which also show the freight edges (highlighted in red) that need to be captured for correctly identifying the parking spot next to freight. Further dimensions for the freight box are available in [28].

**Figure 1.** The design of FURBOT freight box.

The vehicle can load two freight boxes simultaneously, and because of the dimensions of the freight, it loads the freight from the depth edge of the freight (measuring 800 mm, as seen in Figure 1), as shown in Figure 2.

**Figure 2.** Loading of freight.
