Performance Of Robot Research Articles

Investigating the effect of customer-robot interaction experience on customer engagement behavior and co-creation value: a mixed methods study

ABSTRACT This study investigated the effect of robots on customer engagement behavior, employing a mixed methods approach. The qualitative study involved in-depth interviews with a total of 25 customers to explore the effects and constructed a theoretical model. A quantitative investigation then evaluated the proposed model based on a sample of 558 valid respondents. The findings demonstrated that customer interaction with service robots affected customer engagement behavior, through customer perceived hedonic, functional, and symbolic benefits. These effects influenced customer happiness and organizational transaction value, facilitating value co-creation between robots, customers, and firms. The impact of robots on customer engagement behavior was contingent upon travel companions and purpose, but not employee support. This study contributes to the literature by enhancing an understanding of service robot performance and customer engagement behavior, offering practical insights for the effective management of robots in the hotel industry.

Design, Development, and Testing of a Cassava Storage Root-Cutting Robot Utilizing a Stewart Platform and Mask R-CNN for Precision Agriculture

Separating cassava storage root from its stem, known as cassava storage root cutting, represents a pivotal stage in cassava harvesting. It has become increasingly challenging due to a shortage of skilled labor. This research introduces an innovative solution: a cassava storage root-cutting robot (CSRCR) utilizing computer vision technology. The Mask-RCNN model is employed for precise cutting alignment detection. The moving mechanism utilizes a Stewart platform, and the cutting action is performed by a cylinder saw integrated into the robot. The specifications of these components, including dimensions, load capacity, and speed, were meticulously defined and calculated based on a physical survey of cassava plants. The robot's performance was evaluated through a three-step process. First, motion performance was assessed, and the results demonstrated acceptable levels of accuracy, repeatability, and workspace. Second, the optimal moving speed and the cutter's speed were determined. In the third step, the robot was integrated with computer vision technology. The integration achieved a remarkable success rate of 100%. The average loss and trash were minimized to 1.44% and 0.66%, respectively, and the cycle time was 32.43 seconds. This successful integration not only demonstrates the robot's ability to cut cassava stems accurately in various orientations but also significantly improves efficiency by reducing loss and trash. The research findings pave the way for enhanced traditional cassava harvesting practices.

Improving the closing sequences of interaction between human and robot through conversation analysis

This study employs Conversation Analysis to create a recursive model that improves the quality of human-robot interaction. Our research goal is to create a dialogue robot that offers pleasant experiences for users, so they are willing to engage in repeated interactions in daily lives. While there has been dramatic progress in the performance of dialogue robots, there has been less attention to the importance of users’ interactional experience compared to the “specs” of the dialogue system. Employing Goffmanian insights and using research in Conversation Analysis (CA), the present study develops a dialogue closing system to exit the interaction. We then experimentally verified that the robot with the dialogue closing system performs better in the user’s perception of the robot (i.e. likeability, politeness, and dialogue satisfaction) than the control group. Further, by analyzing the dialogue between the human and the robot through CA, we propose to build a recursive, reflective model to improve the dialogue model design. A constructive approach urges us to reproduce complicated social phenomena in human-robot interaction so that we can investigate the underlying cognitive mechanisms of humans and create robots that can convey human-like cognition functions and coexist with humans. Taking such a constructive approach, we posit that our recursive model for dialogue systems that uses CA insights and then qualitatively analyzes conversational data can enhance the quality of dialogue systems because the model elucidates which properties of a conversation humans need to experience a conversational robot as human-like. Our study suggests that interactional morality - particularly conversational closings - is one property of human interactions that humans likely require social robots to adhere to.

A digital design framework for the dimensional optimization of parallel robots based on kinematic and elasto-dynamic performance

The dimensional optimization based on kinematic and dynamic performance indices is proven significant for improving the operational performance of parallel robots. As the pose-dependent performances vary with the dimensional parameters, there are still many challenges in the optimal design of parallel robots, such as the possible conflict amongst different performance indices and computational expensiveness. By considering a 4-DOF high-speed parallel robot as an illustrative example, this paper presents a framework for the optimal design of parallel robots by integrating skeleton modeling, CAD-CAE integration and multi-objective optimization techniques. In this approach, the models for kinematic and elasto-dynamic performance evaluation are first developed using the CAD and CAE techniques, respectively. After evaluating the performance distributions over the task workspace, several reference poses representative of multiple neighboring sample poses are determined to formulate corresponding local performance indices by using the Hard C-Means (HCM) clustering analysis algorithm. This consideration leads to the determination of the optimal dimensions by investigating the Pareto-optimal solutions of a multi-objective optimization problem, allowing the conflict amongst different performance indices to be appropriately handled and the computational time to be saved significantly. The results of the case study show that the proposed approach can significantly enhance the elastic dynamic performance while ensuring that the kinematic performance is not excessively compromised, when compared to the performance of existing physical prototype of the robot. A software package has been developed using the proposed framework, providing a highly accessible way for designing various types of parallel/hybrid robots based on CAD and CAE techniques.

Gait planning of a 4–5R rolling mechanism based on the planar 6R single-loop chain

Abstract. This paper proposes a 4–5R rolling mechanism based on the spatial extension design of a planar 6R single-loop chain. By analyzing the locomotion of the planar equivalent form, a modular gait theory integrating different modes of gait with high efficiency, low energy consumption, and high speed is established. A unified kinematic strategy expression, encapsulated in the form of the gait period table, is tailored for the kinematic chain's gait on the flat terrain. A contrast gait is conducted to ascertain its velocity parameters and volatility of the center of mass (CM). By optimizing the corresponding indicators, two distinct gait patterns are achieved: a faster speed gait that prioritizes increased speed and a steady gait that emphasizes stability with reduced CM volatility. Drawing from the mobility analysis and simulation outcomes of the planar 6R single-loop kinematic chain, a theory of locomotion for a closed-chain linkage mechanism in space is proposed. A locomotion strategy on the flat ground is derived, and a unified evaluation index is proposed. Finally, the feasibility of the two working modes is verified using a physical prototype. The theoretical work in this paper simplifies the design process of closed-chain linkage robots and improves the mobility performance of closed-chain linkage robots. It lays the foundation for researching new types of closed-chain linkage robots.

Basketball robot object detection and distance measurement based on ROS and IBN-YOLOv5s algorithms.

With the combination of artificial intelligence and robotics technology, more and more professional robots are entering the public eye. Basketball robot competition, as a very good target system for autonomous robot research, is very suitable for conducting research on robot autonomous perception system object detection. However, traditional basketball robots have problems such as recognition difficulties, which seriously affect the recognition of robot targets and distance measurement based on recognition. To improve the performance of basketball robots in competitions, research was conducted to improve the object detection system. Firstly, a basketball robot object detection system based on robot operating system was designed. In the software layer of the object detection system, an algorithm that combines YOLOv5s and laser detection was used, and an appropriate instance batch normalization network module was introduced in the YOLOv5s algorithm to improve the model's generalization ability. The experiment outcomes indicated that the improved algorithm had intersection over union (IoU), structural information loss, ambiguity and signal-to-noise ratio of 0.96, 0.03, 0.13, and 0.98, respectively, and performed the best in the other comparison models. The recall curve area and F1 value of the improved algorithm were 0.95 and 0.9789, respectively. In the detection of basketball, volleyball, and calibration columns, the average classification accuracy of the improved model was 95.87%, and the average calibration box accuracy was 97.05%. From this, the algorithm proposed in the study has robust performance and can efficiently achieve object detection and recognition of basketball robots. The improved algorithm proposed in the study provides more reliable and rich information for the perception ability of basketball robots, as well as for their subsequent decision-making and action planning, thereby improving the overall technical level of the robots.

Robust Control Strategy of Acoustic Micro Robots Based on Fuzzy System.

This study presents a robust control strategy for acoustic micro robots utilizing a novel interval type-three fuzzy system. Micro robots driven by acoustic forces face significant challenges in fluid environments due to complex nonlinearities, uncertainties, and disturbances. To address these issues, we propose a control framework that combines fuzzy logic and sliding mode control to enhance the stability and trajectory tracking performance of micro robots under varying fluid conditions. The interval type-3 fuzzy logic system provides increased robustness by better handling external disturbances and uncertainties compared to the robustness of the traditional methods. The experimental results from one-dimensional, two-dimensional, and three-dimensional fluid cavities demonstrate that the proposed control method significantly improves tracking accuracy, reducing the errors in complex environments. This control framework offers promising potential for the precise manipulation of micro robots in biomedical applications and other microfluidic systems. The minimum trajectory tracking control mean square error is 12.82 μm.

Study on the Influence of Wind Load on the Safety of Magnetic Adsorption Wall-Climbing Inspection Robot for Gantry Crane

The maintenance of the surface of steel structures is crucial for ensuring the quality of shipbuilding cranes. Various types of wall-climbing robots have been proposed for inspecting diverse structures, including ships and offshore installations. Given that these robots often operate in outdoor environments, their performance is significantly influenced by wind conditions. Consequently, understanding the impact of wind loads on these robots is essential for developing structurally sound designs. In this study, SolidWorks software was utilized to model both the wall-climbing robot and crane, while numerical simulations were conducted to investigate the aerodynamic performance of the magnetic wall-climbing inspection robot under wind load. Subsequently, a MATLAB program was developed to simulate both the time history and spectrum of wind speed affecting the wall-climbing inspection robot. The resulting wind speed time-history curve was analyzed using a time-history analysis method to simulate wind pressure effects. Finally, modal analysis was performed to determine the natural frequency and vibration modes of the frame in order to ensure dynamic stability for the robot. The analysis revealed that wind pressure predominantly concentrates on the front section of the vehicle body, with significant eddy currents observed on its windward side, leeward side, and top surface. Following optimization efforts on the robot’s structure resulted in a reduction in vortex formation; consequently, compared to pre-optimization conditions during pulsating wind simulations, there was a 99.19% decrease in induced vibration displacement within the optimized inspection robot body. Modal analysis indicated substantial differences between the first six non-rigid natural frequencies of this vehicle body and those associated with its servo motor frequencies—indicating no risk of resonance occurring. This study employs finite element analysis techniques to assess stability under varying wind loads while verifying structural safety for this wall-climbing inspection robot.

Analysis of the effects of interfacial parameters on the thermal conductivity properties of SiC/SMPU composites

AbstractSilicon carbide (SiC)/shape‐memory polyurethane (SMPU) soft robots possess programmable shapes and dual‐drive capabilities based on electrical and thermal methods. Enhancing the thermal conductivity (TC) of these composite materials effectively enhances the driving performance of the soft robots. In this study, we tune the interfacial thickness between SiC particles and the SMPU polymer matrix to regulate the TC of the composites. The optimized composite exhibits a 244% increase in the in‐plane TC and 153% increase in the out‐of‐plane TC. Furthermore, optimization significantly enhances the speed and efficiency of the soft robots. This study reveals that interfacial thickness is a key factor in regulating interfacial heat transfer, potentially introducing a new approach for reducing interfacial thermal resistance in composite materials. This study contributes to a deeper understanding of interfacial heat‐ transfer mechanisms and establishes a new theoretical framework for designing and fabricating advanced composite materials for soft robots.Highlights Interfacial heat‐ transfer mechanism was revealed. Interfacial thickness primarily controls interfacial heat transfer. The in‐plane and out‐of‐plane thermal conductivities of prepared composites were enhanced by 244% and 153%, respectively, by modifying the interfacial thickness. The multifunctional performance of the composites was improved due to microscale mechanisms.

Influence of hydrofoil motion patterns on the hydrodynamic performance of undulating fin for biomimetic underwater robots

The undulatory propulsion of aquatic organisms like the black ghost knifefish offers high manoeuvrability and motion stability, making it a promising model for developing advanced biomimetic underwater robots. However, these robots are frequently hindered by limitations in speed and propulsion efficiency. Inspired by the energy benefits observed in fish schooling, this study introduces a cooperative propulsion system integrating the hydrofoil with the undulating fin to enhance propulsion performance through an investigation of their interaction across various motion patterns. Specifically, we investigate the effects of static, pitching, heaving, and their combination (pitching + heaving) of the hydrofoil on the hydrodynamic performance of the undulating fin. Our results indicate that a static hydrofoil slightly increases the fin's average thrust, while pure pitching marginally reduces it. The high-speed vortices generated by the hydrofoil during pure heaving significantly suppress the fin's thrust. In contrast, the combined motion of pitching and heaving substantially enhances propulsion performance. Thus, the combined motion of the hydrofoil can better enhance the hydrodynamic performance of the undulatory propulsion robot. This study provides a theoretical foundation for the optimized design of high-speed and stable undulating fin propulsion systems, offering valuable insights for developing underwater robots with improved operational capabilities.

Trajectory Planning and Adaptive Fuzzy PID Control for Precision in Robotic Vertebral Plate Cutting: Addressing Force Dynamics and Deformation Challenges

This study explores trajectory planning and cutting force control for spinal surgical robots, focusing on managing cutting deformation and vibration during vertebral plate cutting—a critical challenge in robotic spinal surgery. Through theoretical analysis, simulation, and experimental validation, the research addresses the complexities of cutting force dynamics and the associated deformations. A dynamic equation for vertebral plate cutting is established, providing a theoretical foundation for trajectory planning. A new trajectory planning method using B-spline curves and an interpolation point constraint formula is introduced, enabling precise robot trajectory control. Additionally, an adaptive fuzzy PID control strategy with force feedback is proposed to dynamically adjust the feed rate, effectively suppressing cutting deformation and vibration in real time. Simulations and experiments validate the effectiveness of these methods in reducing force fluctuations and enhancing control stability. The findings offer valuable guidance for improving the performance and safety of spinal surgery robots, optimizing their trajectories, incorporating dynamic sensing, and enhancing safety controls. Future research should focus on refining control strategies for more complex surgical scenarios and validating their applicability under conditions closer to actual surgical environments. This work provides theoretical and practical insights into advancing robotic spinal surgery, contributing to better surgical outcomes and patient safety.

Application and optimisation of intelligent control system for home robots

Abstract. As a significant part of the smart home, intelligent home robots can provide a variety of convenient home services such as automatic cleaning, elderly care, entertainment interaction, etc., which are highly valued and favoured by the majority of home users, and the market scale is expanding. However, the design and optimization of the control system represents a crucial technical challenge to truly realize the intelligence and autonomy of home robots. This paper presents a comprehensive analysis of the design and optimization of automatic control systems for intelligent home robots, which aims to improve the performance and user experience of intelligent home robots and better meet the needs of families. Through collection and analysis of the research on domestic robots and their control technology ,the core technical elements of the control system are summarized and refined, and the hardware structure and software framework of the control system are analyzed. The research results provide valuable insights for improving the performance and capabilities of home robot control systems to better meet the diverse needs and expectations of home users. These innovations provide a solid foundation for advancing the development of intelligent robots in the home. Future trends in control systems may include enhanced perceptual capabilities and decision-making intelligence to enable robots to better understand and meet the needs of home users.

A comparative study of time-related performance: COBOT with industrial robots using digital twin robotic cells

In the context of the industry 4.0, defined by highly personalized processes, there’s a rising interest of technologies related to the extraction of data of the process in real time to better decide future actions i.e. define more efficient and productive configurations of the industrial plant. From this, Cyber-physical systems such as digital twins are the most suited technology to follow the process performance through data and reliably validate different outcomes from simulations. Furthermore, COBOTs that can adapt to the environment are ideal to deal with such changing demands which have to work alongside industrial robots. Therefore, this study aims to use the digital twin capabilities of data extraction and simulation from the FANUC’s robot simulator software to validate the performance of industrial and collaborative robots in order to offer insights to better apply each type of robot. It was used a robotic cell with the robot PRBT 6 as a reference to make 2 digital twins of the cell with 2 different robot models, one collaborative and one industrial. Two digital twins were made using ROBOGUIDE simulator, version 9.4 for the COBOT and version 9.1 for the industrial robot. It’s presented the method used to build the digital twin of the robotic cell and the results show that the cycle time of the COBOT’s cell is significantly higher than the industrial one but has higher flexibility.

Towards a Verifiable Toolchain for Robotics

There is a growing need for autonomous robots to complete complex tasks robustly in dynamic and unstructured environments. However, current robot performance is limited to simple tasks in controlled environments. To improve robot autonomy in complex environments, the robot's deliberation system must be able to synthesise correct plans for a task and generate contingency plans for handling anomalous scenarios that were not expected at design time. The robustness of such a system can be quantified using techniques for formal verification and validation. This paper outlines the progress of EU project CONVINCE (CONtext-aware Verifiable and adaptIve dyNamiC dEliberation), which aims to develop a software toolchain that aids developers in designing, developing, and deploying robot deliberation systems that are fully verified. We describe our modelling approach, each of the toolchain components, and how they interact. We also discuss survey results which demonstrate the demand for a verifiable toolchain among the robotics community.

A survey of offline precision calibration of industrial robots

Abstract. As the need for precision and efficiency grows in industrial manufacturing, the accuracy of industrial robots assumes paramount importance. Nevertheless, factors, such as mechanical structures and assembly processes often introduce errors, compromising robots' positioning and repeatability accuracy. Consequently, precise calibration and compensation of these errors are paramount for optimizing robots performance. A thorough analysis of error sources and the establishment of error models in industrial robots are conducted in the present study, with special attention paid to offline calibration methods. This paper reviews the robot error model building methods and offline accuracy calibration techniques, summarizes the technical difficulties of the calibration task, and proposes the future development direction for the difficulties such as the complexity of error modeling, the difficulty of non-motor calibration calculation, and the traditional stiffness compensation that does not meet the needs of the robot's operation process. The importance of this research lies in its potential to improve the accuracy and reliability of industrial robots, thus contributing to the development of industrial automation.

Multi-Sensor SLAM Positioning and Navigation

This paper provides a comprehensive review of advancements in Positioning and Navigation, focusing on the integration of key technologies to enhance operational efficiency and sustainability. The study examines the application of sensors in robotic systems, with particular emphasis on visual Simultaneous Localization and Mapping (SLAM) and LiDAR SLAM technologies. Visual SLAM, which uses monocular or binocular cameras to capture environmental images for navigation and mapping, offers cost-effective solutions but faces challenges such as sensitivity to lighting conditions and high computational demands. LiDAR SLAM, utilizing laser pulses to create precise 3D maps, complements visual SLAM by improving accuracy and robustness. The review also covers the integration of these technologies with deep learning and other advanced algorithms, highlighting their potential to enhance robotic performance and address practical limitations. The paper identifies future research directions aimed at advancing these technologies for more effective and sustainable practices.

Innovative Solutions for IK: PROA and Clonal Selection Algorithms Unveiled

Calculating joint angles for sequential manipulators consists of studying the correlation between Cartesian and joint variables. The problem-solving technique encounters two main hurdles described as direct and inverse kinematics. Matrix multiplications usually simplify the direct kinematic problem. However, inverse kinematic problems are harder as they require solving many nonlinear equations and eliminating variables a lot. In our work, we introduce two new methods of handling the complicated inverse kinematic problem for robotic manipulator arms; Poor and Rich Optimization Algorithm and Clonal Selection Algorithm (CSA). These advanced techniques enhance greatly the estimation of various joints in the arm which makes the solution more precise and efficient. To demonstrate the effectiveness, robustness, and potential benefits of these approaches for complicated kinematic problems we present extensive simulation results thereby enabling better performance of robots.

Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization

This paper presents an innovative approach that integrates a fixed-time control (FTC) algorithm with an improved sparrow search algorithm (ISSA) to enhance the trajectory tracking accuracy of a two-degree-of-freedom (two-DOF) robotic arm. The FTC algorithm, which incorporates barrier Lyapunov function (BLF) and adaptive neural network strategies, ensures rapid convergence, effective vibration suppression, and the robust handling of system uncertainties and input saturation. The ISSA, inspired by the foraging behavior of sparrows, improves search efficiency through dynamic weight adjustments and chaotic mapping, balancing global and local search capabilities. By optimizing control parameters, ISSA minimizes tracking errors. Simulation results demonstrate that the combined FTC and ISSA approach significantly reduces tracking errors and improves response speed compared to the use of FTC alone, underscoring its potential for achieving high-precision control in robotic arms and offering a promising direction for precise robotic control applications.

Research Progress on Pole-Climbing Robots: A Review

Background: Pole-climbing robots are a type of application robot commonly used for quality inspection, cleaning, and maintenance of utility poles, high voltage lines, bridge cables, transmission pipelines, and other important facilities with a certain height. The working conditions are often harsh and dangerous, making manual participation unsafe. The pole-climbing robot can provide a platform for maintenance and cleaning work. Remote control operation of the pole-climbing robot is achieved through communication and control technology. It has been created to improve efficiency and reduce personnel accidents greatly. At the same time, the continuous development of science and technology has led to the expansion of robot design concepts. It has also brought about great changes and growth in the development of pole-climbing robots. Objective: The purpose of this paper is to report the latest progress in the research of pole-climbing robots from bionic and non-bionic perspectives and to provide a research reference for researchers in this field. Method: By analyzing academic theses and published patents, this paper presents a new classification of pole-climbing robots from the perspective of bionic and non-bionic. By summarizing the literature, the structural characteristics of various pole-climbing robots and their differences and applications are summarized. Results: The performance of the pole-climbing robots is analyzed from the viewpoint of structural characteristics and action execution methods. In turn, the characteristics of various types of pole-climbing robots are summarized. Finally, based on the above discussion, the future problems and development directions of pole-climbing robots are predicted. Conclusion: The pole-climbing robots can be divided into two categories, bionic and non-bionic, based on the analysis of design features. Both bionic and non-bionic pole-climbing robots have good development and applications in their respective directions. Also, bionic and non-bionic pole-climbing robots have different detailed classifications based on material, structure, and other perspectives. They have different advantages and disadvantages in terms of the performance of pole-climbing action execution. It provides a research reference for future researchers in this field.

Enhanced interlocking in granular jamming grippers through hard and soft particle mixtures

We investigate the influence of particle stiffness on the grasping performance of granular grippers, a class of soft robotic effectors that utilize granular jamming for object manipulation. Through experimental analyses and X-ray imaging, we show that grippers with soft particles exhibit improved wrapping of the object after jamming, in contrast to grippers with rigid particles. This results in significantly increased holding force through the interlocking. The addition of a small proportion of rigid particles into a predominantly soft particle mixture maintains the improved wrapping but also significantly increases the maximum holding force. These results suggest a tunable approach to optimizing the design of granular grippers for improved performance in soft robotics applications.Graphic abstract