This review reports the recent state of the art in the field of mobile robots applied to precision agriculture. After a brief introduction to precision agriculture, the review focuses on two main topics. First, it provides a broad overview of the most widely used technologies in agriculture related to crop, field, and soil monitoring. Second, the main robotic solutions, with a focus on land-based robots, and their salient features are described. Finally, a short case study about a robot developed by the authors is introduced. This work aims to collect and highlight the most significant trends in research on robotics applied to agriculture. This review shows that the most studied perception solutions are those based on vision and cloud point detection and, following the same trend, most robotic solutions are small robots dedicated exclusively to monitoring tasks. However, the robotisation of other agricultural tasks is growing.

In the last decades, mobile robotics has become a very interesting research topic in the field of robotics, mainly because of population ageing and the recent pandemic emergency caused by Covid-19. Against this context, the paper presents an overview on wheeled mobile robot (WMR), which have a central role in nowadays scenario. In particular, the paper describes the most commonly adopted locomotion strategies, perception systems, control architectures and navigation approaches. After having analyzed the state of the art, this paper focuses on the kinematics of three omnidirectional platforms: a four mecanum wheels robot (4WD), a three omni wheel platform (3WD) and a two swerve-drive system (2SWD). Through a dimensionless approach, these three platforms are compared to understand how their mobility is affected by the wheel speed limitations that are present in every practical application. This original comparison has not been already presented by the literature and it can be used to improve our understanding of the kinematics of these mobile robots and to guide the selection of the most appropriate locomotion system according to the specific application.

Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle for collective well-being. Despite these emerging needs, in the actual landscape of robotic assistants, there are no platforms that successfully combine reliable mobility in cluttered domestic spaces with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction. In this work, we present Marvin, a novel assistive robotic platform we developed with a modular layer-based architecture, merging a flexible mechanical design with cutting-edge AI for perception and vocal control. We focus the design of Marvin on three target service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. Compared to previous works, we propose a tiny omnidirectional platform, which enables agile mobility and effective obstacle avoidance. Moreover, we design a controllable positioning device, which easily allows the user to access the interface for connectivity and extends the visual range of the camera sensor. Nonetheless, we delicately consider the privacy issues arising from private data collection on cloud services, a critical aspect of commercial AI-based assistants. To this end, we demonstrate how lightweight deep learning solutions for visual perception and vocal command can be adopted, completely running offline on the embedded hardware of the robot.

In recent years, the study of robotic systems for agriculture, a modern research field often shortened as “precision agriculture”, has become highly relevant, especially for those repetitive actions that can be automated thanks to innovative robotic solutions. This paper presents the kinematic model and a motion planning pipeline for a mobile manipulator specifically designed for precision agriculture applications, such as crop sampling and monitoring, formed by a novel articulated mobile base and a commercial collaborative manipulator with seven degrees of freedom. Starting from the models of the two subsystems, characterized by an adjustable position and orientation of the manipulator with respect to the mobile base, the linear mapping that describes the differential kinematics of the whole custom system is expressed as a function of the input commands. To perform pick–and–place tasks, a motion planning algorithm, based on the manipulator manipulability index mapping and a closed form inverse kinematics solution is presented. The motion of the system is based on the decoupling of the base and the arm mobility, and the paper discusses how the base can be properly used for manipulator positioning purposes. The closed form inverse kinematics solution is also provided as an open-source Matlab code.

Thanks to recent developments in service robotics technologies, precision agriculture (PA) is becoming an increasingly prominent research field, and several studies were made to present and outline how the use of mobile robotic systems can help and improve farm production. In this paper, the integration of a custom-designed mobile base with a commercial robotic arm is presented, showing the functionality and features of the overall system for crop monitoring and sampling. To this aim, the motion planning problem is addressed, developing a tailored algorithm based on the so-called manipulability index, that treats the base and robotic arm mobility as two independent degrees of motion; also developing an open source closed-form inverse kinematics algorithm for the kinematically redundant manipulator. The presented methods and sub-system, even though strictly related to a specific mobile manipulator system, can be adapted not only to PA applications where a mobile manipulator is involved but also to the wider field of assistive robotics.

The use of automation and robotics technologies for caregiving and assistance has become a very interesting research topic in the field of robotics. The spread of COVID-19 has highlighted the importance of social distancing in hospitals and health centers, and collaborative robotics can bring substantial improvements in terms of sparing health workers basic operations. Thus, researchers from Politecnico di Torino are working on Paquitop.arm, a mobile robot for assistive tasks. The purpose of this paper is to present a system composed of an omnidirectional mobile platform, a 6 DOF robot arm, and a depth camera. Task-oriented considerations are made to estimate a set of mounting parameters that represents a trade-off between the exploitation of the robot arm workspace and the compactness of the entire system. To this end, dexterity and force transmission indexes are introduced to study both the kinematic and the static behavior of the manipulator as a function of the mounting parameters. Finally, to avoid singularities during the execution of the task, the platform approach to the task workspaces is studied.