Robotics

16 pages, 8264 KiB

Open AccessArticle

Robotized 3D Scanning and Alignment Method for Dimensional Qualification of Big Parts Printed by Material Extrusion

by Juan Carlos Antolin-Urbaneja, Rakel Pacheco Goñi, Nerea Alberdi Olaizola and Ana Isabel Luengo Pizarro

Robotics 2024, 13(12), 175; https://doi.org/10.3390/robotics13120175 - 10 Dec 2024

Abstract

Moulds for aeronautical applications must fulfil highly demanding requirements, including the geometrical tolerances before and after curing cycles at high temperatures and pressures. The growing availability of thermoplastic materials printed by material extrusion systems requires research to verify the geometrical accuracy after three-dimensional [...] Read more.

Moulds for aeronautical applications must fulfil highly demanding requirements, including the geometrical tolerances before and after curing cycles at high temperatures and pressures. The growing availability of thermoplastic materials printed by material extrusion systems requires research to verify the geometrical accuracy after three-dimensional printing processes to assess whether the part can meet the required geometry through milling processes. In this sense, the application of automated techniques to assess quick and reliable measurements is an open point under this promising technology. This work investigates the integration of a 3D vision system using a structured-light 3D scanner, placed onto an industrial robot in an eye-in-hand configuration and synchronized by a computer. The complete system validates an in-house algorithm, which inspects the whole reconstructed part, acquiring several views from different poses, and makes the alignment with the theoretical model of the geometry of big parts manufactured by 3D printing. Moreover, the automation of the validation process for the manufactured parts using contactless detection of the offset-printed material can be used to define milling strategies to achieve the geometric qualifications. The algorithm was tested using several parts printed by the material extrusion of a thermoplastic material based on black polyamide 6 reinforced with short carbon fibres. The complete inspection process was performed in 38 s in the three studied cases. The results assure that more than 95.50% of the evaluated points of each reconstructed point cloud differed by more than one millimetre from the theoretical model. Full article

(This article belongs to the Section Industrial Robots and Automation)

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21 pages, 10733 KiB

Open AccessArticle

CNN-Based Multi-Object Detection and Segmentation in 3D LiDAR Data for Dynamic Industrial Environments

by Danilo Giacomin Schneider and Marcelo Ricardo Stemmer

Robotics 2024, 13(12), 174; https://doi.org/10.3390/robotics13120174 - 9 Dec 2024

Abstract

Autonomous navigation in dynamic environments presents a significant challenge for mobile robotic systems. This paper proposes a novel approach utilizing Convolutional Neural Networks (CNNs) for multi-object detection in 3D space and 2D segmentation using bird’s eye view (BEV) maps derived from 3D Light [...] Read more.

Autonomous navigation in dynamic environments presents a significant challenge for mobile robotic systems. This paper proposes a novel approach utilizing Convolutional Neural Networks (CNNs) for multi-object detection in 3D space and 2D segmentation using bird’s eye view (BEV) maps derived from 3D Light Detection and Ranging (LiDAR) data. Our method aims to enable mobile robots to localize movable objects and their occupancy, which is crucial for safe and efficient navigation. To address the scarcity of labeled real-world datasets, a synthetic dataset based on a simulation environment is generated to train and evaluate our model. Additionally, we employ a subset of the NVIDIA r2b dataset for evaluation in the real world. Furthermore, we integrate our CNN-based detection and segmentation model into a Robot Operating System 2 (ROS2) framework, facilitating communication between mobile robots and a centralized node for data aggregation and map creation. Our experimental results demonstrate promising performance, showcasing the potential applicability of our approach in future assembly systems. While further validation with real-world data is warranted, our work contributes to advancing perception systems by proposing a solution for multi-source, multi-object tracking and mapping. Full article

(This article belongs to the Section AI in Robotics)

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15 pages, 4835 KiB

Open AccessArticle

Optimal Synthesis of Five-Bar Linkage Based on Singularity-Free Workspaces with Predefined Shapes

by Lovasz Erwin-Christian, Ciupe Valentin, Demjen Tivadar, Oarcea Alexandru, Tulcan Elida-Gabriela and Sandu Melania-Olivia

Robotics 2024, 13(12), 173; https://doi.org/10.3390/robotics13120173 - 5 Dec 2024

Abstract

The five-bar linkage, used in the form of a planar manipulator, benefits from easy controllability and relatively simple kinematic structures, which mean that it can be used in several applications in robotics, rehabilitation, and haptic devices, etc. This paper proposes an optimal synthesis [...] Read more.

The five-bar linkage, used in the form of a planar manipulator, benefits from easy controllability and relatively simple kinematic structures, which mean that it can be used in several applications in robotics, rehabilitation, and haptic devices, etc. This paper proposes an optimal synthesis method for a symmetrical five-bar linkage of type 5-RRRRR, with a singularity-free dexterous workspace, based on workspaces with predefined shapes, like squares, rectangles, triangles, circles, and ellipses. The synthesis conditions, to avoid singularities, are given as inequations, which can be further substituted with a system of equations, by introducing the supraunitary coefficient, k. The analytical solutions of the resulting system of equations enable the computation of the link lengths of the five-bar linkage. The optimization method provides the optimal value of the supraunitary coefficient, in order to obtain a maximum value for the minimum input transmission angle and a minimum value for the manipulator size. In this paper, the authors present an analytical approach to the optimal synthesis of a symmetrical five-bar linkage for different shapes of workspace, with the same surface and coordinates in terms of the mass center, as well as the resulting link lengths. In regard to the numerical examples, the authors considered and compared performance indices, such as manipulability, the condition number, and stiffness. The considered examples showed that an equilateral triangle-shaped workspace achieved higher global manipulability, a square-shaped workspace achieved higher global dexterity and the minimum input transmission angle, and circular workspaces achieved the highest mean stiffness and total surface size. It was observed that the synthesis method generates structures that are well-suited to singularity-free dexterous workspaces, with nonzero stiffness values. Full article

(This article belongs to the Section Industrial Robots and Automation)

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33 pages, 24137 KiB

Open AccessArticle

Development of a Reduced-Degree-of-Freedom (DOF) Bipedal Robot with Elastic Ankles

by Sharafatdin Yessirkepov, Michele Folgheraiter, Arman Abakov and Timur Umurzakov

Robotics 2024, 13(12), 172; https://doi.org/10.3390/robotics13120172 - 4 Dec 2024

Abstract

One of the most challenging aspects of designing a humanoid robot is ensuring stable walking. To achieve this, the kinematic architecture must support 3D motion and maintain equilibrium, particularly during single-foot support. Without proper configuration, the robot may experience unbalanced weight distribution, significantly [...] Read more.

One of the most challenging aspects of designing a humanoid robot is ensuring stable walking. To achieve this, the kinematic architecture must support 3D motion and maintain equilibrium, particularly during single-foot support. Without proper configuration, the robot may experience unbalanced weight distribution, significantly increasing the risk of falling while walking. While adding redundant degrees of freedom (DOFs) can enhance adaptability, it also raises the system’s complexity and cost and the need for more sophisticated control strategies and higher energy consumption. This paper explores a reduced-DOF bipedal robot, which, despite its limited number of DOFs, is capable of performing 3D motion. It features an inverted pendulum and elastic ankles made of thermoplastic polyurethane (TPU), enabling effective balance control and attenuation of disturbances. The robot’s electromechanical design is introduced alongside the kinematic model. Momentum equilibrium in a pseudo-static mode is considered in both the frontal and sagittal planes, taking into account the pendulum and the swinging leg during the single support phase. The TPU ankle’s performance is assessed based on its ability to resist external bending forces, highlighting challenges related to the robot’s weight equilibrium stability and ankle inversion. Experimental results from both Finite Element Analysis (FEA) and real-world tests are compared. Lastly, the joint movements of the inverted pendulum-based biped robot are evaluated in both a virtual environment and a physical prototype while performing lateral tilting and various gait sequences. Full article

(This article belongs to the Section Intelligent Robots and Mechatronics)

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30 pages, 15218 KiB

Open AccessArticle

Robust Nonlinear Model Predictive Control for the Trajectory Tracking of Skid-Steer Mobile Manipulators with Wheel–Ground Interactions

by Katherine Aro, Leonardo Guevara, Miguel Torres-Torriti, Felipe Torres and Alvaro Prado

Robotics 2024, 13(12), 171; https://doi.org/10.3390/robotics13120171 - 3 Dec 2024

Abstract

This paper presents a robust control strategy for trajectory-tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimises trajectory-tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy is aimed at counteracting the [...] Read more.

This paper presents a robust control strategy for trajectory-tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimises trajectory-tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy is aimed at counteracting the effects of disturbances caused by the slip phenomena through the wheel–terrain contact and bidirectional interactions propagated by mechanical coupling between the SSMM base and arm. These interactions are modelled using a coupled nonlinear dynamic framework that integrates bounded uncertainties for the mobile base and arm joints. The model is developed based on principles of full-body energy balance and link torques. Then, a centralized control architecture integrates a nominal NMPC (disturbance-free) and ancillary controller based on Active Disturbance-Rejection Control (ADRC) to strengthen control robustness, operating the full system dynamics as a single robotic body. While the NMPC strategy is responsible for the trajectory-tracking control task, the ADRC leverages an Extended State Observer (ESO) to quantify the impact of external disturbances. Then, the ADRC is devoted to compensating for external disturbances and uncertainties stemming from the model mismatch between the nominal representation and the actual system response. Simulation and field experiments conducted on an assembled Pioneer 3P-AT base and Katana 6M180 robotic arm under terrain constraints demonstrate the effectiveness of the proposed method. Compared to non-robust controllers, the R-NMPC approach significantly reduced trajectory-tracking errors by 79.5% for mobile bases and 42.3% for robot arms. These results highlight the potential to enhance robust performance and resource efficiency in complex navigation conditions. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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29 pages, 6762 KiB

Open AccessArticle

Extended Operational Space Kinematics, Dynamics, and Control of Redundant Serial Robots

by Edward J. Haug, Vincent De Sapio and Adrian Peidro

Robotics 2024, 13(12), 170; https://doi.org/10.3390/robotics13120170 - 30 Nov 2024

Abstract

A recently developed differential geometric representation of redundant serial robot kinematics is employed to create a new extended operational space dynamics and control formulation that explicitly accounts for redundant robot degrees of freedom. This formulation corrects deficiencies in kinematics and dynamics of redundant [...] Read more.

A recently developed differential geometric representation of redundant serial robot kinematics is employed to create a new extended operational space dynamics and control formulation that explicitly accounts for redundant robot degrees of freedom. This formulation corrects deficiencies in kinematics and dynamics of redundant serial robots that have relied for over half a century on error-prone generalized inverse velocity-based kinematics for redundancy resolution. New ordinary differential equations of robot operational space dynamics are obtained, without the need for ad hoc derivation, in terms of task coordinates and self-motion coordinates that represent robot redundancy. A new extended operational space control approach is presented that exploits ordinary differential equations of motion in terms of task and self-motion coordinates, enabling enforcement of desired output trajectories, obstacle avoidance, and performance constraints. Four examples are presented with a one-degree-of-redundancy robot that demonstrate the validity and superior performance of the new formulation, relative to the traditional task space method used for redundant serial robot control. Finally, an example with eight degrees of redundancy is presented that further illustrates superior performance of the new operational space formulation. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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12 pages, 6888 KiB

Open AccessArticle

How AI from Automated Driving Systems Can Contribute to the Assessment of Human Driving Behavior

by Tom Driessen, Olger Siebinga, Thomas de Boer, Dimitra Dodou, Dick de Waard and Joost de Winter

Robotics 2024, 13(12), 169; https://doi.org/10.3390/robotics13120169 - 21 Nov 2024

Abstract

This paper proposes a novel approach to measuring human driving performance by using the AI capabilities of automated driving systems, illustrated through three example scenarios. Traditionally, the assessment of human driving has followed a bottom-up methodology, where raw data are compared to fixed [...] Read more.

This paper proposes a novel approach to measuring human driving performance by using the AI capabilities of automated driving systems, illustrated through three example scenarios. Traditionally, the assessment of human driving has followed a bottom-up methodology, where raw data are compared to fixed thresholds, yielding indicators such as the number of hard braking events. However, acceleration threshold exceedances are often heavily influenced by the driving context. We propose a top-down context-aware approach to driving assessments, in which recordings of human-driven vehicles are analyzed by an automated driving system. By comparing the human driver’s speed to the AI’s recommended speed, we derive a level of disagreement that can be used to distinguish between hard braking caused by aggressive driving and emergency braking in response to a critical event. The proposed method may serve as an alternative to the metrics currently used by some insurance companies and may serve as a template for future AI-based driver assessment. Full article

(This article belongs to the Section AI in Robotics)

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30 pages, 10077 KiB

Open AccessArticle

Design and Experimental Evaluation of Multiple 3D-Printed Reduction Gearboxes for Wearable Exoskeletons

by Riccardo Bezzini, Giulia Bassani, Carlo Alberto Avizzano and Alessandro Filippeschi

Robotics 2024, 13(11), 168; https://doi.org/10.3390/robotics13110168 - 19 Nov 2024

Abstract

The recent advancements in wearable exoskeletons have highlighted their effectiveness in assisting humans for both rehabilitation and augmentation purposes. These devices interact with the user; therefore, their actuators and power transmission mechanisms are crucial for enhancing physical human–robot interaction (pHRI). The advanced progression [...] Read more.

The recent advancements in wearable exoskeletons have highlighted their effectiveness in assisting humans for both rehabilitation and augmentation purposes. These devices interact with the user; therefore, their actuators and power transmission mechanisms are crucial for enhancing physical human–robot interaction (pHRI). The advanced progression of 3D printing technology as a valuable method for creating lightweight and efficient gearboxes enables the exploration of multiple reducer designs. However, to the authors’ knowledge, only sporadic implementations with relatively low reduction ratios have been reported, and the respective experimental validations usually vary, preventing a comprehensive evaluation of different design and implementation choices. In this paper, we design, develop, and examine experimentally multiple 3D-printed gearboxes conceived for wearable assistive devices. Two relevant transmission ratios (1:30 and 1:80) and multiple designs, which include single- and double-stage compact cam cycloidal drives, compound planetary gearboxes, and cycloidal and planetary architectures, are compared to assess the worth of 3D-printed reducers in human–robot interaction applications. The resulting prototypes were examined by evaluating their weight, cost, backdrivability, friction, regularity of the reduction ratio, gear play, and stiffness. The results show that the developed gearboxes represent valuable alternatives for actuating wearable exoskeletons in multiple applications. Full article

(This article belongs to the Special Issue AI for Robotic Exoskeletons and Prostheses)

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20 pages, 9893 KiB

Open AccessArticle

Context-Specific Navigation for ‘Gentle’ Approach Towards Objects Based on LiDAR and URF Sensors

by Claudia Álvarez-Aparicio, Beáta Korcsok, Adrián Campazas-Vega, Ádám Miklósi, Vicente Matellán and Bence Ferdinandy

Robotics 2024, 13(11), 167; https://doi.org/10.3390/robotics13110167 - 19 Nov 2024

Abstract

Navigation skills are essential for most social and service robotics applications. The robots that are currently in practical use in various complex human environments are generally very limited in their autonomous navigational abilities; while they can reach the proximity of objects, they are [...] Read more.

Navigation skills are essential for most social and service robotics applications. The robots that are currently in practical use in various complex human environments are generally very limited in their autonomous navigational abilities; while they can reach the proximity of objects, they are not efficient in approaching them closely. The new solution described in this paper presents a system to solve this context-specific navigation problem. The system handles locations with differing contexts based on the use of LiDAR and URF sensors, allowing for the avoidance of people and obstacles with a wide margin, as well as for approaching target objects closely. To quantify the efficiency of our solution we compared it with the ROS contextless standard navigation (move_base) in two different robot platforms and environments, both with real-world tests and simulations. The metrics selected were (1) the time the robot needs to reach an object, (2) the Euclidean distance, and (3) the orientation between the final position of the robot and the defined goal position. We show that our context-specific solution is superior to the standard navigation both in time and Euclidean distance. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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29 pages, 27816 KiB

Open AccessArticle

Trajectory Aware Deep Reinforcement Learning Navigation Using Multichannel Cost Maps

by Tareq A. Fahmy, Omar M. Shehata and Shady A. Maged

Robotics 2024, 13(11), 166; https://doi.org/10.3390/robotics13110166 - 17 Nov 2024

Abstract

Deep reinforcement learning (DRL)-based navigation in an environment with dynamic obstacles is a challenging task due to the partially observable nature of the problem. While DRL algorithms are built around the Markov property (assumption that all the necessary information for making a decision [...] Read more.

Deep reinforcement learning (DRL)-based navigation in an environment with dynamic obstacles is a challenging task due to the partially observable nature of the problem. While DRL algorithms are built around the Markov property (assumption that all the necessary information for making a decision is contained in a single observation of the current state) for structuring the learning process; the partially observable Markov property in the DRL navigation problem is significantly amplified when dealing with dynamic obstacles. A single observation or measurement of the environment is often insufficient for capturing the dynamic behavior of obstacles, thereby hindering the agent’s decision-making. This study addresses this challenge by using an environment-specific heuristic approach to augment the dynamic obstacles’ temporal information in observation to guide the agent’s decision-making. We proposed Multichannel Cost Map Observation for Spatial and Temporal Information (M-COST) to mitigate these limitations. Our results show that the M-COST approach more than doubles the convergence rate in concentrated tunnel situations, where successful navigation is only possible if the agent learns to avoid dynamic obstacles. Additionally, navigation efficiency improved by 35% in tunnel scenarios and by 12% in dense-environment navigation compared to standard methods that rely on raw sensor data or frame stacking. Full article

(This article belongs to the Section AI in Robotics)

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18 pages, 6281 KiB

Open AccessArticle

Mechanical Design, Manufacturing, and Testing of a Soft Pneumatic Actuator with a Reconfigurable Modular Reinforcement

by Michele Gabrio Antonelli, Pierluigi Beomonte Zobel, Enrico Mattei and Nicola Stampone

Robotics 2024, 13(11), 165; https://doi.org/10.3390/robotics13110165 - 12 Nov 2024

Abstract

Soft actuators have enabled the growth of soft robotics, overcoming several drawbacks of rigid robotics by providing devices with many degrees of freedom and the ability to grasp, bend, move, jump, and more. The reconfiguration of the workspace is still a limitation of [...] Read more.

Soft actuators have enabled the growth of soft robotics, overcoming several drawbacks of rigid robotics by providing devices with many degrees of freedom and the ability to grasp, bend, move, jump, and more. The reconfiguration of the workspace is still a limitation of these actuators. Indeed, once the actuator is designed and developed, it is used for a specific task. This work presents a reconfigurable soft pneumatic actuator with a novel reconfigurable modular reinforcement. The latter is wrapped around an inner tube in silicone rubber and is made of components whose assembly can be configured based on the task. A formulation is identified by a hybrid approach based on finite element analysis and response surface methodology for predicting and designing the behavior of the actuator. The prototyping revealed the ease of fabrication and reconfigurability as the strength of this new actuator. The experimental tests demonstrated the feasibility of adopting the actuator as a finger in a gripper for handling and moving objects of different shapes, masses, and stiffness. Furthermore, the evaluated performance shows a good trade-off between mass, developed force, implementation time, easy reconfigurability, and cost-effectiveness. Full article

(This article belongs to the Special Issue Advanced Grasping and Motion Control Solutions, Edition II)

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21 pages, 5673 KiB

Open AccessArticle

HaptiScan: A Haptically-Enabled Robotic Ultrasound System for Remote Medical Diagnostics

by Zoran Najdovski, Siamak Pedrammehr, Mohammad Reza Chalak Qazani, Hamid Abdi, Sameer Deshpande, Taoming Liu, James Mullins, Michael Fielding, Stephen Hilton and Houshyar Asadi

Robotics 2024, 13(11), 164; https://doi.org/10.3390/robotics13110164 - 10 Nov 2024

Abstract

Medical ultrasound is a widely used diagnostic imaging modality that provides real-time imaging at a relatively low cost. However, its widespread application is hindered by the need for expert operation, particularly in remote regional areas where trained sonographers are scarce. This paper presents [...] Read more.

Medical ultrasound is a widely used diagnostic imaging modality that provides real-time imaging at a relatively low cost. However, its widespread application is hindered by the need for expert operation, particularly in remote regional areas where trained sonographers are scarce. This paper presents the development of HaptiScan, a state-of-the-art telerobotic ultrasound system equipped with haptic feedback. The system utilizes a commercially available robotic manipulator, the UR5 robot from Universal Robots, integrated with a force/torque sensor and the Phantom Omni haptic device. This configuration enables skilled sonographers to remotely conduct ultrasound procedures via an internet connection, addressing both the geographic and ergonomic limitations faced in traditional sonography. Key innovative features of the system include real-time force feedback, ensuring that sonographers can precisely control the ultrasound probe from a remote location. The system is further enhanced by safety measures such as over-force sensing, patient discomfort monitoring, and emergency stop mechanisms. Quantitative indicators of the system’s performance include successful teleoperation over long distances with time delays, as demonstrated in simulations. These simulations validate the system’s control methodologies, showing stable performance with force feedback under varying time delays and distances. Additionally, the UR5 manipulator’s precision, kinematic, and dynamic models are mathematically formulated to optimize teleoperation. The results highlight the effectiveness of the proposed system in overcoming the technical challenges of remote ultrasound procedures, offering a viable solution for real-world telemedicine applications. Full article

(This article belongs to the Special Issue Development of Biomedical Robotics)

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20 pages, 27274 KiB

Open AccessArticle

Subtask-Based Usability Evaluation of Control Interfaces for Teleoperated Excavation Tasks

by Takumi Nagate, Hikaru Nagano, Yuichi Tazaki and Yasuyoshi Yokokohji

Robotics 2024, 13(11), 163; https://doi.org/10.3390/robotics13110163 - 9 Nov 2024

Abstract

This study aims to experimentally determine the most suitable control interface for different subtasks in the teleoperation of construction robots in a simulation environment. We compare a conventional lever-based rate control interface (“Rate-lever”) with two alternative methods: rate control (“Rate-3D”) and position control [...] Read more.

This study aims to experimentally determine the most suitable control interface for different subtasks in the teleoperation of construction robots in a simulation environment. We compare a conventional lever-based rate control interface (“Rate-lever”) with two alternative methods: rate control (“Rate-3D”) and position control (“Position-3D”), both using a 3D positional input device. In the experiments, participants operated a construction machine in a virtual environment and evaluated the control interfaces across three tasks: sagittal plane excavation, turning, and continuous operation. The results revealed that “Position-3D” outperformed others for sagittal excavation, while both “Rate-lever” and “Rate-3D” were more effective for turning. Notably, “Position-3D” and “Rate-3D” can be implemented on the same input device and are easily integrated. This feature offers the possibility of a hybrid-type interface suitable for operators to obtain optimized performance in sagittal and horizontal tasks. Full article

(This article belongs to the Special Issue Robot Teleoperation Integrating with Augmented Reality)

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24 pages, 2730 KiB

Open AccessArticle

Robust and Adaptive Control of a Soft Continuum Manipulator for Minimally Invasive Surgery

by Liujia Wang, Kaiwen Chen and Enrico Franco

Robotics 2024, 13(11), 162; https://doi.org/10.3390/robotics13110162 - 7 Nov 2024

Abstract

This article investigates the model-based control in configurations space of a soft continuum manipulator for minimally invasive surgery. The main control challenges for these types of systems are the presence of model uncertainties and nonlinearities. To this end, a sliding-mode controller, a Lyapunov [...] Read more.

This article investigates the model-based control in configurations space of a soft continuum manipulator for minimally invasive surgery. The main control challenges for these types of systems are the presence of model uncertainties and nonlinearities. To this end, a sliding-mode controller, a Lyapunov redesign controller, and an adaptive controller have been designed and compared by means of simulations and experiments on a prototype. The results indicate that the adaptive controller yields better accuracy but a slower transient. Conversely, the sliding-mode controller and Lyapunov redesign yield a faster response but can result in chattering or steady-state errors. Full article

(This article belongs to the Special Issue Adaptive and Nonlinear Control of Robotics)

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12 pages, 2009 KiB

Open AccessArticle

The Effectiveness of a Robotic Workstation Simulation Implementation in the Automotive Industry Using a Closed-Form Solution of the Absolute Orientation Problem

by Wojciech Andrzej Szulc and Piotr Czop

Robotics 2024, 13(11), 161; https://doi.org/10.3390/robotics13110161 - 30 Oct 2024

Abstract

This paper provides an in-depth analysis of a novel methodology to enhance the commissioning processes of robotic production lines in the automotive sector, with a particular emphasis on the implementation of offline programming (OLP) methods. The proposed innovative methodology, verified within the automotive [...] Read more.

This paper provides an in-depth analysis of a novel methodology to enhance the commissioning processes of robotic production lines in the automotive sector, with a particular emphasis on the implementation of offline programming (OLP) methods. The proposed innovative methodology, verified within the automotive industry, introduces a systematic, iterative process for calibrating and aligning the local user coordinate system (UCS) with high-precision external measurements, ensuring minimal discrepancy between simulated and actual robot paths. A significant contribution of this study is an original adjustment of the numerical algorithm applying a closed-form solution to the absolute orientation problem where unit quaternions are used to establish a UCS and evaluate positioning errors. The experimental validation study draws from 485 measurement datasets gathered across more than 300 robot stations, with each dataset comprising at least six measured point pairs, using readings from both internal robot positioning systems and a Leica AT403 laser tracker, aligned with nominal tooling values. This approach addresses discrepancies between simulated and actual environments, and our findings show an 83.51% success rate for direct implementation of simulated robot path programs. This result underscores the effectiveness of the proposed method and demonstrates the accuracy of the developed numerical algorithm, providing a reliable measure of real OLP implementation effectiveness in the automotive sector. This method further streamlines multi-robot station setup through centralized UCS alignment, significantly reducing commissioning time and enhancing efficiency in both the assembly and commissioning stages of robotized production lines. The proposed methodology facilitates precise alignment in the commissioning stage and highlights the need for synchronized simulation updates, robust offline programming practices, and regular kinematic error verification to further enhance OLP accuracy. Full article

(This article belongs to the Special Issue Integrating Robotics into High-Accuracy Industrial Operations)

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17 pages, 1170 KiB

Open AccessArticle

Telepresence Robots in the Context of Dementia Caregiving: Caregivers’ and Care Recipients’ Perspectives

by Shabnam FakhrHosseini, Lauren Cerino, Lisa D’Ambrosio, Lexi Balmuth, Chaiwoo Lee, Mengke Wu and Joseph Coughlin

Robotics 2024, 13(11), 160; https://doi.org/10.3390/robotics13110160 - 30 Oct 2024

Abstract

As a result of a rapidly aging population and the increasing prevalence of dementia among older adults, technological solutions are increasingly being considered to facilitate caregiving. This research investigates the perspectives of 20 caregiving dyads on VGo, a telepresence social robot with features [...] Read more.

As a result of a rapidly aging population and the increasing prevalence of dementia among older adults, technological solutions are increasingly being considered to facilitate caregiving. This research investigates the perspectives of 20 caregiving dyads on VGo, a telepresence social robot with features designed to support caregiving. Care recipients (CRs), aged 65 and older, diagnosed with Alzheimer’s disease and related dementias, along with their primary caregivers (CGs), evaluated the robot through an online interview study. The interviews integrated informative videos showcasing VGo’s features and functions. Insights from the interviews revealed diverse expectations, interests, and reservations. The majority of CGs and their CRs perceived the robot’s features as beneficial. In particular, the voice command capability was appreciated as an alternative to using smartphones and as a way to manage home appliances. The community feature, however, did not align well with many participants’ lifestyles, and participants had a number of suggestions to enhance the robot’s notification function. Based on the interview results, the study offers a set of design recommendations for telepresence social robots in home caregiving contexts. This investigation highlights the promise of social robots in caregiving contexts and underscores the need for further improvements to ensure they fit users’ needs. Full article

(This article belongs to the Special Issue Social Robots for the Human Well-Being)

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22 pages, 9800 KiB

Open AccessArticle

Arduino-Based Mobile Robotics for Fostering Computational Thinking Development: An Empirical Study with Elementary School Students Using Problem-Based Learning Across Europe

by Rolando Barradas, José Alberto Lencastre, Salviano Pinto Soares and António Valente

Robotics 2024, 13(11), 159; https://doi.org/10.3390/robotics13110159 - 29 Oct 2024

Abstract

The present article explores the impact of educational robotics on fostering computational thinking and problem-solving skills in elementary school students through a problem-based learning approach. This study involved the creation of a framework which includes a robot and two eBooks designed for students [...] Read more.

The present article explores the impact of educational robotics on fostering computational thinking and problem-solving skills in elementary school students through a problem-based learning approach. This study involved the creation of a framework which includes a robot and two eBooks designed for students and teachers. The eBooks serve as a guide to the construction and programming of a small Arduino-based robot. Through integration with gamification elements, the model features a narrative with three characters to boost a student’s engagement and motivation. Through iteration of heuristic evaluations and practical tests, we refined the initial theoretical framework. An empirical study was conducted in two phases involving 350 students. The first empirical test involved a small group of 21 students, similar to end users, from five European schools. With a 100% completion rate for the tasks, 73.47% of these tasks were solved optimally. Later, we conducted a larger validation study which involved 329 students in a Portuguese school. This second phase of the study was conducted during the 2022–2023 and 2023–2024 school years with three study groups. The results led to a 91.13% success rate in problem-solving activities, and 56.99% of those students achieved optimal solutions. Advanced statistical techniques, including ANOVA, were applied to account for group differences and ensure the robustness of the findings. This study demonstrates that the proposed model which integrates educational robotics with problem-based learning effectively promotes computational thinking and problem-solving skills, which are essential for the 21st century. These findings support the inclusion of robotics into primary school curricula and provide a validated framework for educators. Full article

(This article belongs to the Special Issue Advances and Challenges in Educational Robotics, Volume III)

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24 pages, 4188 KiB

Open AccessArticle

Methodology for Integrated Design Optimization of Actuation Systems for Exoskeletons

by Daniel Greve and Christian Kreischer

Robotics 2024, 13(11), 158; https://doi.org/10.3390/robotics13110158 - 25 Oct 2024

Abstract

The engineering of actuation systems for active exoskeletons presents a significant challenge due to the stringent demands for mass reduction and compactness, coupled with complex specifications for actuator dynamics and stroke length. This challenge is met with a model-based methodology. Models for human [...] Read more.

The engineering of actuation systems for active exoskeletons presents a significant challenge due to the stringent demands for mass reduction and compactness, coupled with complex specifications for actuator dynamics and stroke length. This challenge is met with a model-based methodology. Models for human body, exoskeleton and parametric actuation systems are derived and coupled. Beginning with an inverse dynamics human body simulation, loads in human joints are estimated, and the corresponding support torques are derived. Under the assumption of a control law ensuring these support torques, an optimization problem is stated to determine actuation system parameters such as the number of stator coils and number of battery cells. Lastly, results from the optimization are validated using sophisticated models. The methodology is applied to an exemplary exoskeleton and compared to an approach derived from previous studies. Full article

(This article belongs to the Section Neurorobotics)

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19 pages, 8123 KiB

Open AccessArticle

Towards a Unified Framework for Software-Hardware Integration in Evolutionary Robotics

by Edgar Buchanan, Léni K. Le Goff, Matthew F. Hale, Emma Hart, Agoston E. Eiben, Matteo De Carlo, Mike Angus, Robert Woolley, Jon Timmis, Alan F. Winfield and Andy M. Tyrrell

Robotics 2024, 13(11), 157; https://doi.org/10.3390/robotics13110157 - 25 Oct 2024

Abstract

The discrepancy between simulated and hardware experiments, the reality gap, is a challenge in evolutionary robotics. While strategies have been proposed to address this gap in fixed-body robots, they are not viable when dealing with populations and generations where the body is in [...] Read more.

The discrepancy between simulated and hardware experiments, the reality gap, is a challenge in evolutionary robotics. While strategies have been proposed to address this gap in fixed-body robots, they are not viable when dealing with populations and generations where the body is in constant change. The continual evolution of body designs necessitates the manufacturing of new robotic structures, a process that can be time-consuming if carried out manually. Moreover, the increased manufacturing time not only prolongs hardware experimental durations but also disrupts the synergy between hardware and simulated experiments. Failure to effectively manage these challenges could impede the implementation of evolutionary robotics in real-life environments. The Autonomous Robot Evolution project presents a framework to tackle these challenges through a case study. This paper describes the main three contributions of this work: Firstly, it analyses the different reality gap experienced by each different robot or the heterogenous reality gap. Secondly, it emphasizes the importance of automation in robot manufacturing. And thirdly, it highlights the necessity of a framework to orchestrate the synergy between simulated and hardware experiments. In the long term, integrating these contributions into evolutionary robotics is envisioned to enable the continuous production of robots in real-world environments. Full article

(This article belongs to the Special Issue Progress and Prospects of Evolutionary Robotics)

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