Design and Control of a Novel High Payload Light Arm for Heavy Aerial

Manipulation Tasks

Michele Marolla, Jonathan Cacace

and Vincenzo Lippiello

CREATE Consortium and PRISMA Lab, Department of Engineering and Information Technology,

University of Naples Federico II, via Claudio 21, Naples, Italy

Keywords:

Aerial Manipulation, Robotic Arm, Inspection and Maintenance.

Abstract:

Aerial manipulation is a rapidly emerging research ﬁeld that explores the use of Unmanned Aerial Vehicles as

mobile manipulators. To enable aerial manipulation, UAVs must be equipped with lightweight robotic arms

capable of interacting with the environment. However, due to battery life constraints and payload limitations,

these arms must be designed to be as light as possible, which restricts their ability to transport and manipulate

heavy objects. In this work, we introduce a novel aerial manipulator prototype designed speciﬁcally for high

payload manipulation. The arm is designed to have its center of mass as close as possible to its base, which is

attached to the aerial frame. The arm incorporates a system of belts to facilitate the movement of its various

joints. This paper presents the arm’s design, along with a control approach to compensate for the elasticity

introduced by the belts. To showcase the system’s capabilities, we conduct two sets of experiments. Firstly,

the arm is tested within a controlled laboratory environment. Secondly, we deploy an aerial robot equipped

with the proposed prototype in a powerline maintenance task.

1 INTRODUCTION

Over the past decade, the utilization of Unmanned

Aerial Vehicles (UAVs) has seen remarkable success

across various industries and applications. UAVs

have been effectively employed in diverse ﬁelds in-

cluding search and rescue operations (Cacace et al.,

2016) (Sibanyoni et al., 2019) (Mishra et al., 2020),

industrial building inspection (Cacace et al., 2013),

inspection and maintenance tasks (Uzakov et al.,

2020) (Tosato et al., 2019), surveillance, remote sens-

ing, and more. Notably, there has been a recent ad-

vancement in aerial systems that enables them to un-

dertake operations involving direct interaction with

the environment, such as grasping and piercing (Rug-

giero et al., 2018). This development has proven in-

valuable in handling industrial and service applica-

tions that are either deemed hazardous or too intri-

cate for human operators. The evolution of aerial ma-

nipulation capabilities has led to the introduction of

a wide array of platforms (Ollero et al., 2022), rang-

ing from ﬁxed propeller conﬁgurations (Cano et al.,

2014) (Tognon et al., 2019) to tilting (Tognon et al.,

2019) or tilted multi-copters (Franchi, 2019). Re-

https://orcid.org/0000-0002-1639-5655

https://orcid.org/0000-0002-6089-2333

Figure 1: Proposed manipulator mounted under an Un-

manned Aerial Vehicle during an electrical power line main-

tenance task.

gardless of the actuation type, the aerial manipulators

share a critical component: their robotic arm. A fun-

damental concern in aerial manipulation is striking a

balance between the arm’s functionality and the con-

straints imposed by the UAV’s battery life and pay-

Marolla, M., Cacace, J. and Lippiello, V.

Design and Control of a Novel High Payload Light Arm for Heavy Aerial Manipulation Tasks.

DOI: 10.5220/0012202900003543

In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2023) - Volume 1, pages 465-473

ISBN: 978-989-758-670-5; ISSN: 2184-2809

465

load limitations. Achieving optimal performance re-

quires designing lightweight robotic arms that retain

adequate strength and dexterity. This delicate trade-

off between weight and capability presents a substan-

tial challenge, as lighter arms may encounter difﬁcul-

ties in efﬁciently transporting and manipulating heav-

ier objects. Overcoming this limitation is essential

for broadening the scope of tasks that aerial manip-

ulators can effectively accomplish. Recent advance-

ments in Aerial Manipulation Robots have showcased

their capability to perform diverse operations, such as

object grasping (Suarez et al., 2018), sensor installa-

tion and retrieval (Suarez et al., 2020), contact-based

inspection (Trujillo et al., 2019), and execution of var-

ious tasks using grippers and other tools (Shimahara

et al., 2016). The integration of these manipulators

in multi-rotors has led to the development of numer-

ous prototypes, including multijoint arms (Bellicoso

et al., 2015), dual-arm systems (Suarez et al., 2018),

linear actuators (Hamaza et al., 2019), delta manip-

ulators (Chermprayong et al., 2019), compliant joint

arms (Suarez et al., 2020), long-reach aerial manip-

ulators (Miyazaki et al., 2020), and even three-arm

manipulators that serve both as object grippers and

reconﬁgurable landing gear (Paul et al., 2019). For an

aerial manipulation robot to efﬁciently interact with

the environment, it must possess two crucial charac-

teristics: a lightweight structure and a high payload

lifting capacity. For this reason, we propose the de-

velopment and experimental validation of a new mor-

phology of an aerial manipulation robot arm consist-

ing of extremely light structure, capable of lifting and

manipulating a heavy weight (See Figure 1). The ac-

tuation mechanism is based on a group of belts for

the ﬁrst joints and a group of servo motors for the arm

wrist. The belt system has been chosen to allow the

placement of the main motor group close to the base

of the arm. However, the presence of the belts in-

duces elasticity in the arm motion, particularly when

it is stretched. For this reason, a control technique

exploiting a couple of inertial sensors placed on the

arm structure is used to compensate such elasticity,

improving the precision of the end effector during the

operations.

The prototype’s effectiveness has been demon-

strated through two comprehensive tests. The initial

test focused on assessing the elasticity compensation

controller in a controlled laboratory setting. By com-

paring the arm’s motion with and without the com-

pensation, the objective was to evaluate its perfor-

mance. The second test took place in a test bed fa-

cility, where the arm was integrated into an aerial sys-

tem. During this test, a maintenance task involving

an electrical power line was successfully executed,

showcasing the arm’s practical functionality under

real-world conditions.

To summarize, this work presents signiﬁcant con-

tributions, including (i) The development of an inno-

vative lightweight manipulator designed speciﬁcally

for aerial manipulation tasks, featuring remarkable

payload lifting capabilities. This design ensures op-

timal performance while adhering to the weight con-

straints imposed by aerial systems. (ii) The intro-

duction of a control approach aimed at effectively

compensating for elasticity in the proposed arm dur-

ing motion tasks. This compensatory mechanism en-

hances the precision and stability of the arm’s move-

ments, thereby improving its overall performance.

The rest of the paper is organized as follows. In

Section 2 the motivational use case in which the pro-

posed solution has been used is described. In Sec-

tion 3 the mechanical and electrical speciﬁcations of

the arm are discussed and in Section 4 the arm elas-

ticity compensation is introduced. The software ar-

chitecture to control the proposed arm is presented in

Section 5. Finally, the system at work is shown in

Section 6. Finally, we include an appendix section to

report the hardware adopted in the design of the arm.

2 MOTIVATION

This work is primarily motivated by the need for

high payload manipulation in various tasks preva-

lent today. Particularly, it draws inspiration from the

experimental use case proposed by the Aerial-Core

(AERIAL COgnitive integrated multi-task Robotic

system with Extended operation range and safety)

H2020 project (Cacace and et al., 2021). The project

aims to leverage the ﬂying capabilities of UAVs for

inspecting and maintaining power grids, involving ac-

tivities such as landing and perching on energy lines,

as depicted in Figure 1. The tasks entail installing and

removing various devices from the power lines (IEEE,

2009), including bird diverters (helical and clip di-

verters) used to prevent bird collisions, which pose

a threat to both avian life and the power infrastructure

or electrical cable spacers. Additionally, the power

lines are exploited to improve the efﬁciency of the

aerial system. In particular, a recharging stations may

need to be installed to extend the UAVs’ battery life.

These tasks often require specialized end-effectors

and introduce additional payload to the robotic arm.

For instance, a tool to carry out helical bird diverter

manipulation is presented in (Cacace et al., 2023). In

particular, in the latter work, a unique tool speciﬁcally

designed to remove helical bird diverters from power

lines.

ICINCO 2023 - 20th International Conference on Informatics in Control, Automation and Robotics

466

(a)

(b)

Figure 2: Overview of the proposed arm with (a) the IMU

sensors and (b) detail of the spherical wrist.

Another approach to addressing general power

lines maintenance is discussed in the work by (Suarez

et al., 2023). They propose a lightweight dual arm

system that can be transported along the power line to

perform maintenance operations. However, it is im-

portant to note that the payload capacity and force ex-

erted by their device are relatively low compared to

the solution proposed in this work.

3 MANIPULATOR DESIGN

The main objective of this paper is to showcase the

development of an articulated robotic arm capable

of executing various demanding tasks in multiple

aerial manipulation scenarios. These tasks encom-

pass object grasping, device installation and retrieval,

contact-based inspection, and more.

The manipulator proposed in this work is an an-

thropomorphic arm featuring six Degrees of Free-

dom (DoFs), accompanied by a gear-based spherical

wrist that serves as the end effector. This conﬁgura-

tion is essential to achieve a superior level of dexter-

ity, enabling the arm to successfully accomplish all

the designated tasks. The last joint of the arm has

been thoughtfully designed with a versatile ﬂange, al-

lowing for easy attachment of different end-effectors

speciﬁcally tailored to carry out speciﬁc tasks.

The proposed robotic arm has been designed to

weigh 3 kg, making it lightweight and agile. Despite

its compact size, it boasts an impressive payload ca-

pacity of 5 kg when fully extended. This remarkable

payload/weight ratio of 1.67 > 1 sets it apart from

other similar solutions proposed in the literature.

The ability to achieve such a high payload/weight

ratio is a crucial and distinguishing feature of this

robotic arm. It enables the arm to be effectively de-

ployed on aerial systems, where tasks often require

either substantial interaction forces or the handling of

heavy payloads. By surpassing the payload/weight

ratios of alternative solutions found in the literature,

this arm proves to be an exceptional choice for aerial

manipulation scenarios that demand both robust force

application and efﬁcient payload transport.

However, due to the high payload/weight ratio, the

resultant arm motion is quite limited. Speciﬁcally, the

maximum velocity achievable by the end-effector is

within the range of 5 to 20 cm/s, depending on the

speciﬁc conﬁguration of the arm. While this may im-

pose some constraints, it is important to note that the

primary application scenario where the proposed so-

lution excels is when the aerial system is perched on

a surface before initiating the manipulation task. The

design of the arm takes inspiration from the Hadding-

ton Dynamics Dexter HDI

, with notable modiﬁca-

tions tailored to enhance its performance. One signif-

icant alteration involves the placement of one of the

motors responsible for controlling the wrists. This

motor has been strategically positioned in line with

the connection between the ﬁrst and second link, as

illustrated in Figure 3b. This design serves multiple

purposes. Firstly, it enables a more balanced and even

distribution of the arm’s weight, ensuring optimal sta-

bility during operation. Secondly, by eliminating the

need for additional components such as belts, pulleys,

and bearings, the overall weight of the arm is signiﬁ-

cantly reduced. This reconﬁguration of the wrist mo-

tor placement not only improves weight distribution,

but also contributes to a more efﬁcient and stream-

lined design. The reduction in the number of compo-

nents leads to enhanced reliability and ease of mainte-

nance. Additionally, it allows for a more compact and

lightweight robotic arm without compromising on its

strength and functionality.

There are other systems available in the market

that share similarities with the one proposed in this

work. One notable example is the Dexter HDI, in-

troduced earlier, and another comparable system is

the UR3 from Universal Robots

. In order to pro-

https://www.hdrobotic.com/

https://www.universal-robots.com/products/

ur3-robot/

Design and Control of a Novel High Payload Light Arm for Heavy Aerial Manipulation Tasks

467

(a)

(b)

Figure 3: Motor disposition along the arm. (a) Brushless

motors for the arm, (b) servo motors for the wrist.

vide a comprehensive analysis, Table 1 compares the

proposed arm with these commercial robotic arms.

It is important to note that while the proposed arm

may have certain disadvantages in speciﬁc application

areas, it remains competitive, particularly in terms

of payload capacity. It is worth acknowledging that

the proposed solution competes favorably in the mar-

ket, despite being potentially disadvantaged in certain

comparison aspects due to the nature of its particular

application area. The focus on payload capacity is a

strength of the proposed arm, enabling it to excel in

tasks requiring substantial payload handling. In addi-

tion, the proposed solution is lighter (to be transported

from an aerial system) and the power requirement is

lower.

3.1 Mechanical Description

The arm has been designed considering two kinds of

motors, depending on the type of joint to control and

the demanded torque. In particular, the ﬁrst three mo-

tors are brushless motors, while the spherical wrist is

composed of three servo motors (see Fig. 3). Also,

the actuation type depends on the positioning of the

motor along the arm structure and, in particular, the

Figure 4: Cad section of the spherical wrist design.

ﬁrst joint is actuated directly by the motor, and the

link is attached to the motor’s output ﬂange. The sec-

ond joint is actuated by the motor coupled with a har-

monic drive transmission to guarantee a reduction ra-

tio of 1:100. Finally, the third joint is actuated by the

motor coupled with a harmonic drive transmission to

guarantee a reduction ratio of 1:80, while it uses a

belt-pulley mechanism to actuate the forearm. During

the design process, the FEA (Finite Element Analy-

sis) has been conducted. Each part of the arm has

been designed with the same approach, using a ﬁrst

layer forming the structure of the overall dimensions,

and a second layer made by a thin element realized

in strong material (carbon ﬁber or aluminum). This

provides structural resistance to the robot, while guar-

anteeing at the same time the required lightness. The

analysis demonstrated that carbon ﬁber layers work

properly, absorbing a great part of the stress. As for

the spherical wrist, it has been designed in steel and

a section is shown in Figure 4. The three wrist joints

are actuated using servomotors and belts.

3.2 Electrical Description

The power unit of the robotic arm is thoughtfully inte-

grated within the manipulator base, contributing to a

neat and self-contained system. To activate the arm, a

24 V power supply unit is required, providing the nec-

essary electrical energy. In terms of communication,

the arm establishes an Ethernet connection with an

external controller, typically a standard laptop. This

communication link allows for seamless interaction

and control of the arm’s operations. Further informa-

ICINCO 2023 - 20th International Conference on Informatics in Control, Automation and Robotics

468

Table 1: Comparison between commercial robot arms and the proposed solution.

Dexter HDI UR3e Proposed arm

Robot weight [kg] 6 11.2 3

Reach [mm] 700 500 700

Payload [kg] 3 3 5

Power requirements [W] 40 - 100 100 - 300 50

Joint ranges [deg] Base

Pivot

Shoulder

Differential

Gripper

360

270

180

360

300

Base

Shoulder

Wrist1

Wrist2

Wrist3

360

Base

Shoulder

Elbow

Wrist1

Wrist2

Wrist3

360

180

270

360

End effector included Yes No No

tion regarding the system architecture can be found in

Section 5.

The ﬁrmware implementation, responsible for di-

rectly controlling the hardware, is executed on an

on-board microcontroller. This microcontroller efﬁ-

ciently handles communication with the motors and

sensors, ensuring accurate and real-time control of

the arm’s movements. To consolidate the electronic

components and optimize space utilization, a com-

pact custom-made Printed Circuit Board (PCB) is em-

ployed, providing a centralized platform for the nec-

essary electronics. Additionally, a fuse is incorpo-

rated into the system design to protect against short-

circuits, promptly interrupting the power supply in

such instances and safeguarding the overall system.

As previously mentioned, the arm has been de-

signed with versatility in mind, enabling it to work

with various tools and end-effectors. To facilitate ef-

fortless integration of these tools, their servomotors

can be easily connected in a daisy-chain conﬁguration

to the wrist control motors. The microcontroller intel-

ligently detects and manages these connected tools,

allowing for seamless switching between different

tools during operation. This ﬂexibility and modularity

enhance the arm’s adaptability to diverse task require-

ments.

Furthermore, the arm incorporates two Inertial

Measurement Units (IMUs), strategically placed on

the wrist and elbow. These IMUs provide valuable

data to the microcontroller, which utilizes it to com-

pensate for elasticity caused by the belts and the high

payload of the arm. By actively compensating for

elasticity, the arm achieves more precise and accu-

rate movements, ensuring optimal performance. For

a more comprehensive understanding of the elastic-

ity compensation method employed, refer to Section 4

for detailed information.

4 ELASTICITY COMPENSATION

As already stated, the utilization of belt transmis-

sions in the arm introduces inherent challenges related

to elasticity. While transient behavior can be toler-

ated due to the arm’s limited velocity, steady-state er-

rors may still occur. These errors become more pro-

nounced as the payload weight increases and the arm

extends further. Given that the proposed arm is specif-

ically designed for heavy tasks, such as manipulating

objects weighing up to 5 kg, it is imperative to address

this issue. Failure to do so can result in signiﬁcant

displacement of the end effector caused by elasticity,

rendering it incapable of autonomously executing as-

signed motion tasks.

To tackle this problem, our solution incorporates

two IMUs strategically positioned on the wrist and el-

bow of the arm. These IMUs are installed at the end

of the second and third links of the arm, as depicted in

Figure 2 (a). By leveraging the data provided by these

IMUs, it becomes possible to accurately calculate the

real orientation of the arm’s links and the precise posi-

tion of the end effector. This information enables the

implementation of corrective measures, allowing the

arm to successfully execute tasks even in the presence

of elasticity.

Given that the arm motors are controlled in veloc-

ity, the computation of the commanded velocity for

the i-th motor is based on the desired position q

d,i

the i-th link and the current position q

measured by

the motor’s encoder.

d,i

= G

r,i

∗ K

p,i

∗ ˜q

(1)

where G

r,i

is the gear ratio of the transmission linked

to the motor i, K

p,i

is a proportional gain conveniently

tuned, and ˜q

= q

d,i

− q

is the error between the de-

sired link orientation and the orientation given by the

Design and Control of a Novel High Payload Light Arm for Heavy Aerial Manipulation Tasks

469

motor encoder also considering the mechanical trans-

mission.

Due to the elasticity, the real orientation q

of the

i-th link is different from the q

read by the motor’s

encoder. For this reason, there will be an error at

steady-state that the system is not aware of. Consider

now the value q

read by the IMU: this represents the

real orientation of the i-th link.

The equation of the commanded velocity be-

comes:

d,i

= G

r,i

∗ K

p,i

∗

ˆq

(2)

where

ˆq

= q

d,i

− q

is the error between the de-

sired orientation and the one read by the IMU. The

implementation of elasticity compensation, as previ-

ously described, is executed on the on-board micro-

controller and can be activated or deactivated through

commands sent by the main companion computer. By

adopting this approach, the correction algorithm re-

mains transparent to the high-level controller and tra-

jectory planner, allowing for seamless integration into

the overall system. The microcontroller takes charge

of establishing communication with the IMUs and ap-

plies a low-pass ﬁlter to the measurements obtained

from them. This ﬁltering process helps to reﬁne the

accuracy of the data used for elasticity compensation.

Additionally, a security layer is incorporated to han-

dle potential issues such as missing or noisy measure-

ments from the IMUs. If such situations occur, the se-

curity layer activates, halting the correction algorithm

and reverting back to the standard controller. This im-

plementation of elasticity compensation has proven to

be highly effective in mitigating the effects of elas-

ticity caused by high payloads. It ensures the arm

is capable of successfully accomplishing the required

tasks, as discussed in Section 6. By enabling precise

and reliable compensation, the arm can maintain the

desired trajectory and achieve the desired level of per-

formance.

5 SYSTEM ARCHITECTURE

This section provides an overview of the system archi-

tecture implemented to successfully control the arm.

The architecture comprises two main layers, each

serving a speciﬁc purpose, and is outlined in Figure 5.

The ﬁrst layer consists of the Controllers, which

are implemented on an external companion com-

puter running a standard GNU/Linux operating sys-

tem. This layer leverages the Robot Operating Sys-

tem (ROS) (Joseph and Cacace, 2018) as the robotic

middleware. Within this layer, two distinct types

of controllers have been developed. The ﬁrst con-

troller enables motion control in the arm’s joint space,

known as Direct Joint Control. It allows precise con-

trol over individual joints, facilitating intricate move-

ments. The second controller enables control of the

arm in the operational space, known as Inverse Ki-

netic Control. This controller utilizes the Kinematics

and Dynamics Library (KDL), enabling precise con-

trol of the arm’s position and orientation in the opera-

tional space.

At a lower level, the system hardware is controlled

by a custom ﬁrmware installed on a microcontroller.

This ﬁrmware is responsible for implementing the

communication protocol with the brushless and servo

motors used in the arm. Through this communication

protocol, the ﬁrmware allows commanding the posi-

tion and velocity of the motors, while retrieving their

current state as output. In addition to motor control,

this layer incorporates essential safety checks to en-

sure compliance with joint and velocity limits, pre-

venting any potential violations. Furthermore, this

layer includes a conﬁguration storage system, which

stores a set of pre-planned conﬁgurations. These con-

ﬁgurations are utilized to set up the arm for different

operations, such as an initial manipulation conﬁgu-

ration or a closing transporting conﬁguration. In ad-

dition, in this layer are implemented all the needed

value transformation to translate joint commands into

motor commands, taking into account gear rations

and motor coupling.

To establish communication between the compan-

ion computer and the microcontroller, a custom net-

work interface is employed. This network interface

utilizes an Ethernet connection, facilitating reliable

and efﬁcient data transmission between the two com-

ponents of the system.

The hardware chosen for the development of the

mechatronic system is listed in the following.

• Three T-Motor motors Ak60 have been selected

for the ﬁrst three elements of the arm. The com-

munication protocol has been implemented using

the CAN standard

• The spherical wrist is composed of Dynamixel

MX28-AT 2.0 servomotors, communicating with

the RS485 protocol

• The WitMotion WT61C inertial sensors have been

used for the elasticity compensation, with the TTL

communication protocol.

• The microcontroller connecting the compound

computer and the system hardware is based on the

ST STM32F767ZI microcontroller

ICINCO 2023 - 20th International Conference on Informatics in Control, Automation and Robotics

470

Figure 5: System architecture.

6 EXPERIMENTS

The system under examination has been tested in two

different operational scenarios, each providing differ-

ent insights into its performance and capabilities.

In the ﬁrst case, the arm was subjected to testing

within a controlled indoor facility. This facility was

equipped with an OptiTrack

motion capture system,

used to accurately track the arm’s movements. By

employing this motion capture system, the position

of the manipulator’s end-effector relative to its base

throughout various motions has been tracked. As for

the second test case, the arm has been tested in a real-

world experiment. In this scenario, the arm was posi-

tioned downward in an aerial system that was perched

over a power line cable. This setup aimed to simu-

late a practical application where the arm needed to

be deployed in an elevated and potentially hazardous

environment.

A video showing the execution of those experi-

ments can be found at: http://y2u.be/vDPNLvIjPpo.

6.1 Case Study 1

In this particular test case, the robotic arm was ﬁrmly

secured to a stable ground structure to eliminate any

external factors that could affect its motion. To simu-

late a practical scenario, a device weighing 2 kg was

Figure 6: Laboratory site to test the proposed manipulator

in the elasticity compensation task.

https://optitrack.com/

attached to the end effector of the arm. This additional

payload introduces challenges related to elasticity and

requires effective compensation strategies to maintain

precise control.

To assess the performance of the control approach,

an operational space trajectory consisting of four

waypoints was planned. To ensure smooth and con-

tinuous motion, a ﬁfth-order spline was used to in-

terpolate between the waypoints. The trajectory was

executed twice: once with the elasticity compensation

enabled and once without it. This comparative anal-

ysis enables a direct evaluation of the impact of the

compensation technique on the arm’s ability to accu-

rately follow the desired trajectory.

During the motion task, the OptiTrack motion

capture system was employed to track the position of

the end effector relative to the base frame of the arm.

This high-precision tracking system provides accurate

and reliable measurements of the arm’s actual motion.

The results of the motion capture system were

analyzed and compared between the two modalities,

with and without elasticity compensation. Figure 7

illustrates the recorded motion displacement, clearly

highlighting the differences between the compensated

and uncompensated motions. Notably, the z-axis,

Figure 7: Laboratory test using a motion capture system to

estimate the effect of the elasticity compensation during the

operations.

Design and Control of a Novel High Payload Light Arm for Heavy Aerial Manipulation Tasks

471

Figure 8: Real world experiment tests case: installation of a particular tool on a power line. (a) Approaching, (b) tool inserting,

which is most affected by the presence of the attached

payload, exhibits a more signiﬁcant displacement.

These detailed observations and comparisons pro-

vide valuable insights into the effectiveness of the

control approach, speciﬁcally in compensating for the

elasticity induced by the payload. By evaluating the

differences in motion between the two modalities, the

arm’s performance and the efﬁcacy of the compensa-

tion strategy can be accurately assessed and validated.

6.2 Case Study 2

The second test case has been carried out in the

ATLAS Experimental Flight Center

located in the

Southern Spain. In this test, the aerial system is

perched on a power line cable, while the arm is used

to hold a recharging station on the same cable. This is

a representative task of the Aerial Core project and, in

particular, such a station is used to charge the batter-

ies of the UAV during the inspection operations, ex-

ploiting the electricity of the power grid. The weight

of the station is around 3.5 kg and consists of a bat-

tery charger and two clamps with a housing for the

power cable. In addition, the station is actuated in or-

der to close its clamps around the cable. The goal of

the aerial manipulator in this case, was to correctly

deploy the charger station on the power line. An ex-

ample of this process is depicted in Figure 8, where

the main steps of the task are depicted, from an initial

task conﬁguration, to the installation of the device on

the cable.

7 CONCLUSIONS

This work introduces a novel design concept for

a lightweight manipulator speciﬁcally engineered to

handle heavy aerial manipulation tasks. One key fea-

https://atlascenter.aero/en/

ture of this design is the strategic placement of the

Center of Mass, situated as close as possible to the

arm base. This conﬁguration enhances the arm’s

portability, making it well-suited for transportation

using ﬂying systems.

The primary actuation mechanism employed in

this manipulator is based on a set of belts. How-

ever, this choice introduces challenges in achieving

precise motion at the tip of the manipulator due to

the inherent elasticity of the belt system. This behav-

ior becomes particularly prominent when the arm is

subjected to heavy payloads. To address this issue, a

control approach is proposed to mitigate the effects of

elasticity during arm motion. This approach, coupled

with the overall system design, aims to optimize the

arm’s performance and ensure accurate and reliable

manipulation tasks.

The main case study for evaluating the proposed

arm is within the domain of the Aerial Core EU

project. In this project, the aerial arm is speciﬁcally

employed for inspection and maintenance operations

of electrical power grids. This real-world application

showcases the practical signiﬁcance and potential of

the proposed system in addressing critical infrastruc-

ture challenges.

To validate the effectiveness of the proposed sys-

tem, both laboratory tests and real-world experiments

have been conducted. These experiments include the

transportation of a 3.5 kg payload, demonstrating the

arm’s capability to handle substantial loads and per-

form precise operations. The results of these tests

highlight the system’s performance and its potential

impact in real-world scenarios.

Moving forward, the future direction of this work

involves an extensive evaluation of the arm’s capa-

bilities, focusing on more qualitative analysis. This

entails further investigations and assessments to com-

prehensively understand the arm’s performance char-

acteristics, enabling reﬁnement and enhancement of

its capabilities for a wider range of applications.

ICINCO 2023 - 20th International Conference on Informatics in Control, Automation and Robotics

472

ACKNOWLEDGEMENTS

The research leading to these results has been sup-

ported by the AERIAL-CORE project (Horizon 2020

Grant Agreement No. 871479). The authors are

solely responsible for its content.

REFERENCES

Bellicoso, C. D., Buonocore, L. R., Lippiello, V., and Si-

ciliano, B. (2015). Design, modeling and control of a

5-dof light-weight robot arm for aerial manipulation.

In 2015 23rd Mediterranean Conference on Control

and Automation (MED), pages 853–858.

Cacace, J. and et al. (2021). Safe local aerial manipulation

for the installation of devices on power lines: Aerial-

core ﬁrst year results and designs. Applied Sciences,

11(13).

Cacace, J., Finzi, A., Lippiello, V., Furci, M., Mimmo, N.,

and Marconi, L. (2016). A control architecture for

multiple drones operated via multimodal interaction

in search rescue mission. In 2016 IEEE International

Symposium on Safety, Security, and Rescue Robotics

(SSRR), pages 233–239.

Cacace, J., Finzi, A., Lippiello, V., Loianno, G., and San-

zone, D. (2013). Aerial service vehicles for indus-

trial inspection: Task decomposition and plan execu-

tion. In Ali, M., Bosse, T., Hindriks, K. V., Hoogen-

doorn, M., Jonker, C. M., and Treur, J., editors, Recent

Trends in Applied Artiﬁcial Intelligence, pages 302–

311, Berlin, Heidelberg. Springer Berlin Heidelberg.

Cacace, J., Giampetraglia, L., Ruggiero, F., and Lippiello,

V. (2023). A novel gripper prototype for helical bird

diverter manipulation. Drones, 7(1).

Cano, R., Perez, C., Prua

no, F., Ollero, A., and Heredia, G.

(2014). Mechanical design of a 6-dof aerial manipu-

lator for assembling bar structures using uavs.

Chermprayong, P., Zhang, K., Xiao, F., and Kovac, M.

(2019). An integrated delta manipulator for aerial re-

pair: A new aerial robotic system. IEEE Robotics &

Automation Magazine, 26(1):54–66.

Franchi, A. (2019). Platforms with Multi-directional Total

Thrust, pages 53–65. Springer International Publish-

ing, Cham.

Hamaza, S., Georgilas, I., Fernandez, M., Sanchez, P.,

Richardson, T., Heredia, G., and Ollero, A. (2019).

Sensor installation and retrieval operations using an

unmanned aerial manipulator. IEEE Robotics and Au-

tomation Letters, 4(3):2793–2800.

IEEE (2009). Guide for maintenance methods on energized

power lines. Std 516-2009, pages 1–144.

Joseph, L. and Cacace, J. (2018). Mastering ROS for

Robotics Programming - Second Edition: Design,

Build, and Simulate Complex Robots Using the Robot

Operating System. Packt Publishing, 2nd edition.

Mishra, B., Garg, D., Narang, P., and Mishra, V. (2020).

Drone-surveillance for search and rescue in natural

disaster. Computer Communications, 156:1–10.

Miyazaki, R., Paul, H., Kominami, T., and Shimonomura,

K. (2020). Wire-suspended device control based

on wireless communication with multirotor for long

reach-aerial manipulation. IEEE Access, 8:172096–

172104.

Ollero, A., Tognon, M., Suarez, A., Lee, D., and Franchi,

A. (2022). Past, present, and future of aerial

robotic manipulators. IEEE Transactions on Robotics,

38(1):626–645.

Paul, H., Miyazaki, R., Ladig, R., and Shimonomura, K.

(2019). Landing of a multirotor aerial vehicle on an

uneven surface using multiple on-board manipulators.

In 2019 IEEE/RSJ International Conference on Intel-

ligent Robots and Systems (IROS), pages 1926–1933.

Ruggiero, F., Lippiello, V., and Ollero, A. (2018). Aerial

manipulation: A literature review. IEEE Robotics and

Automation Letters, 3(3):1957–1964.

Shimahara, S., Leewiwatwong, S., Ladig, R., and Shimono-

mura, K. (2016). Aerial torsional manipulation em-

ploying multi-rotor ﬂying robot. In 2016 IEEE/RSJ

International Conference on Intelligent Robots and

Systems (IROS), pages 1595–1600.

Sibanyoni, S. V., Ramotsoela, D. T., Silva, B. J., and

Hancke, G. P. (2019). A 2-d acoustic source localiza-

tion system for drones in search and rescue missions.

IEEE Sensors Journal, 19(1):332–341.

Suarez, A., Heredia, G., and Ollero, A. (2018). Design of

an anthropomorphic, compliant, and lightweight dual

arm for aerial manipulation. IEEE Access, 6:29173–

29189.

Suarez, A., Nekoo, S. R., and Ollero, A. (2023). Ultra-

lightweight anthropomorphic dual-arm rolling robot

for dexterous manipulation tasks on linear infras-

tructures: A self-stabilizing system. Mechatronics,

94:103021.

Suarez, A., Real, F., Vega, V. M., Heredia, G., Rodriguez-

Casta

no, A., and Ollero, A. (2020). Compliant bi-

manual aerial manipulation: Standard and long reach

conﬁgurations. IEEE Access, 8:88844–88865.

Tognon, M., Ch

avez, H. A. T., Gasparin, E., Sabl

e, Q.,

Bicego, D., Mallet, A., Lany, M., Santi, G., Re-

vaz, B., Cort

es, J., and Franchi, A. (2019). A truly-

redundant aerial manipulator system with application

to push-and-slide inspection in industrial plants. IEEE

Robotics and Automation Letters, 4(2):1846–1851.

Tosato, P., Facinelli, D., Prada, M., Gemma, L., Rossi, M.,

and Brunelli, D. (2019). An autonomous swarm of

drones for industrial gas sensing applications. In 2019

IEEE 20th International Symposium on ”A World of

Wireless, Mobile and Multimedia Networks” (WoW-

MoM), pages 1–6.

Trujillo, M. A., Martinez-de Dios, J. R., Martin, C., Vig-

uria, A., and Ollero, A. (2019). Novel aerial manip-

ulator for accurate and robust industrial ndt contact

inspection: A new tool for the oil and gas inspection

industry. Sensors, 19(6).

Uzakov, T., Nascimento, T. P., and Saska, M. (2020). Uav

vision-based nonlinear formation control applied to

inspection of electrical power lines. In 2020 Inter-

national Conference on Unmanned Aircraft Systems

(ICUAS), pages 1301–1308.

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