Multi-rotor Aerial Vehicles in Physical Interactions: A Survey

Abstract: Research on Multi-rotor Aerial Vehicles (MAVs) has experienced remarkable advancements over the past two decades, propelling the field forward at an accelerated pace. Through the implementation of motion control and the integration of specialized mechanisms, researchers have unlocked the potential of MAVs to perform a wide range of tasks in diverse scenarios. Notably, the literature has highlighted the distinctive attributes of MAVs that endow them with a competitive edge in physical interaction when compared to other robotic systems. In this survey, we present a categorization of the various types of physical interactions in which MAVs are involved, supported by comprehensive case studies. We examine the approaches employed by researchers to address different challenges using MAVs and their applications, including the development of different types of controllers to handle uncertainties inherent in these interactions. By conducting a thorough analysis of the strengths and limitations associated with different methodologies, as well as engaging in discussions about potential enhancements, this survey aims to illuminate the path for future research focusing on MAVs with high actuation capabilities.

• The paper surveys diverse physical interaction types for multi-rotor aerial vehicles, including rigid, soft, hybrid, and non-contact methods.
• The paper evaluates key control strategies such as PID, adaptive, and optimal control to manage challenges in physical interactions.
• The paper highlights future directions focusing on collaborative, modular designs and improvements in energy efficiency and agility.

Introduction

Multi-rotor Aerial Vehicles (MAVs) have seen significant advancements in recent years, particularly in their ability to engage in physical interactions with the environment. These interactions distinguish MAVs from other robotic systems due to their unique design and control capabilities that allow three-dimensional movement and hovering. This paper surveys the various types of physical interactions involving MAVs and assesses methodologies, challenges, and potential enhancements.

Characteristics and Suitability

MAVs, unlike fixed-wing aircraft or ground vehicles, can hover and navigate in all axes of three-dimensional space. Compared to other aerial vehicles, MAVs have simple designs and controllers, are agile and scalable, and can engage in various field applications. The primary roles suitable for MAVs, given their unique characteristics, center around tasks that require flexible deployment, payload carrying, and trajectory following. However, MAVs typically have lower energy efficiency and are not optimized for high-speed flight.

Types of Physical Interaction

The study categorizes the physical interactions of MAVs into multiple groups based on the rigidity of the models and contact involved. These groups include rigid interactions, such as attaching rigid manipulators or directly using the MAV body; soft interactions, which involve deformable components like ropes, bendables, and elastics; hybrid interactions that encompass different phases with various rigidity; and interactions with no contact, often enabled by specialized equipment for sensing and environmental data collection.

Control Strategies

Controlling MAVs in physical interactions can be challenging due to uncertainties and disturbances. The paper evaluates several control strategies utilized to address these challenges. PID (Proportional-Integral-Derivative) control and feedback linearization are common for their computational efficiency and simplicity. Adaptive control compensates for parameter uncertainty, while optimal control is preferred for including actuation constraints and objectives in highly structured tasks. Learning-based control, although less prevalent, can be effective in highly unstructured environments.

Future Directions and Development

The survey sees the future of MAVs in collaborative physical interactions and modular designs, leading to increased robustness and adaptability. There is an emphasis on potential improvements in MAVs' energy efficiency and operational speed. Additionally, to meet the advancing demands in robotics, future research will likely focus on enhancing MAV interaction capabilities, including better control methods that consider the scalability and redistributed actuation.

Conclusion

Overall, this paper presents a comprehensive study on MAVs engaged in different types of physical interactions. It outlines the wider potential of MAVs beyond traditional flight, focusing on how they interact with their environment in novel and beneficial ways. The study suggests a collaborative and modular approach for future research, with MAVs continuing to evolve as key players in the expanding field of robotics.