Robot Applications Research Articles

Improved 3D laser point cloud reconstruction for autonomous mobile robot applications by using SVM-R technique

PurposeIn autonomous mobile robots, high-level accuracy and precision in 3D perception are required for object detection, shape estimation and obstacle distance measurement. However, the existing methods suffer from limitations like inaccurate point clouds, noise in sensor data and synchronization problems between 2D LiDAR and servomotor. These factors can lead to the wrong perception and also introduce noise during sensor registration. Thus, the purpose of this study is to address these limitations and enhance the perception in autonomous mobile robots.Design/methodology/approachA new sensor mounting structure is developed for 3D mapping by using a 2D LiDAR and servomotor. The proposed method uses a support vector machine regression (SVM-R) technique to optimize the waypoints of the servomotor for the point cloud reconstruction process and to obtain a highly accurate and detailed representation of the environment.FindingsThe study includes an analysis of the SVM-R model, including Linear, radial basis function (RBF) and Polynomial kernel. Results show that the Linear kernel performs better with the lowest 3.67 mean absolute error (MAE), 26.24 mean squared error (MSE) and 5.12 root mean squared error (RMSE) values than the RBF and Polynomial kernels. The 2D to 3D point cloud reconstruction shows that the proposed method with a new sensor mounting structure performs better in perception accuracy and achieves an error of 0.45% in measuring the height of the target objects whereas in previous techniques the error was very large.Originality/valueThe study shows the effectiveness of SVM-R in the 3D point cloud reconstruction process and exhibits remarkable performance for object height measurement. Further, the proposed technique is applicable for future advanced visual applications and has a superior performance over the other conventional methods.

The Role of Service Robots in Restaurant Settings: A Meta-Analysis Study on Consumer Behavior and Intentions

The employment of service robots in restaurants has become increasingly common. Previous studies have explored the factors related to the impact of service robots on consumers from multiple perspectives, but this topic still lacks an integrated empirical study to organize and analyze the conclusions of previous studies. This study obtained 46 empirical studies through the WoS and Scopus databases. Based on the conclusions and data of these studies and guided by the SOR theory, a holistic conceptual framework was constructed to describe how service robots affect restaurant consumers. This study tested the conceptual framework of the construct through meta-analysis and verified the moderating role of macro variables such as time and culture. This study not only has theoretical significance for future research but can also provide practical guidance for restaurant managers in the application and deployment of service robots.

Gait Sensors with Customized Protruding Structures for Quadruped Robot Applications

Gait Sensors with Customized Protruding Structures for Quadruped Robot Applications

Stakeholder Perspectives on Safety Issues in Collaborative Mobile Robots: A Case Study of Quadruped Robot Applications in a Smart Factory

Stakeholder Perspectives on Safety Issues in Collaborative Mobile Robots: A Case Study of Quadruped Robot Applications in a Smart Factory

Sharp Curve Trajectory Tracking of a Universal Omni-Wheeled Mobile Robot Using a Sliding Mode Controller

Abstract In our previous works, Amarasiri et al. (2022, “Robust Dynamic Modeling and Trajectory Tracking Controller of a Universal Omni-Wheeled Mobile Robot,” ASME Lett. Dyn. Sys. Control 2(4), p. 040902) and Amarasiri et al. (2024, “Investigating Suitable Combinations of Dynamic Models and Control Techniques for Offline Reinforcement Learning Based Navigation: Application of Universal Omni-Wheeled Robots,” ASME Lett. Dyn. Sys. Control 4(2), p. 021007), two dynamic models of a universal omni-wheeled mobile robot (UOWMR), and trajectory-tracking controllers (three linear and one nonlinear) were developed and presented. The purpose of that work was to identify suitable combinations of dynamic models and trajectory-tracking controllers, choosing the combination with the highest tracking accuracy and the lowest solver execution time. The ultimate purpose is to utilize these physics-based tools in a reinforcement learning (RL) agent developed for path planning and navigation in an unstructured environment. Three trajectories were investigated including a smooth path, a sharp curved path, and a smooth path with disturbance forces. The sliding mode controller (SMC) following a trajectory with sharp (right-angled) curves was not investigated in that work. The sharp corners caused indeterminacy in the path derivatives required for the SMC algorithm. In this short article, we complete our studies of the SMC on sharp corner paths utilizing slight trajectory corner smoothing.

Automation in Agriculture: A Robotic Approach to Weed Control for Greenhouse Cucumber Cultivation

The increasing global population has heightened the demand for efficient food production, leading to the adoption of compact cultivation methods such as greenhouses. However, weed growth within these controlled environments significantly challenges crop productivity. The application of robots can be a useful and economic choice. This study presents an innovative, purely mechanical system for weed control in greenhouses, specifically designed to operate autonomously on a monorail. The machine stops in the distance between the two main plant rows (cucumber) and its arm goes into the gap to deploy the weeds by rotating its blades. This is continued repeatedly. The cutting is by the rotational speed of the blade. Variable-speed motions of the blade were at 3500, 2500 and 1500 rpm for 3 types of moulinex, triangular, and circular blades. The movement speed of the arm was 10 and 30 rpm and the forward movement speed of the machine was 30, 40, 50, 60, 80 and 120 rpm. The results showed that different blades, blade speeds and engine speed affect significantly (p <0.05) the percentage of weeds being cut. Although the interactions of these factors have no significant effect on percentage; the average percentages by the blades have significant differences. Although the interactions between these factors were not statistically significant, the comparison of means revealed that at lower blade speeds, the blade type had a pronounced effect on weed-cutting efficiency. As blade speed increased, differences in blade performance diminished. The most effective combination was achieved using Moulinex blades at 3500 rpm with a 10-rpm arm speed, resulting in the highest percentage of weeds cut. These findings suggest that optimizing blade type and speed can significantly enhance the mechanical weed control efficiency in greenhouse environments.

Industrial Robots, Factor Market Distortion, and Productivity

ABSTRACTWe find that robot adoption significantly increases firm‐level TFP, but factor market distortion hinders the promotion effect of robot adoption on firm‐level TFP. Mechanism analysis reveals that the cost‐saving and labor productivity improvements brought about by industrial robot application stimulate market entry by new firms and elevate the exit risk for incumbent enterprises. This dynamic intensifies competition, resulting in an enhanced market environment that contributes to firm‐level TFP. However, factor market distortions impede the survival of the fittest among firms and stifle the competitive effects of market entry and exit. This ultimately leads to sluggish growth in firm‐level TFP.

Robotic uro-oncology applications of SSI Mantra™ robot

Robotic uro-oncology applications of SSI Mantra™ robot

Effect of Upper Robot-Assisted Training on Upper Limb Motor, Daily Life Activities, and Muscular Tone in Patients With Stroke: A Systematic Review and Meta-Analysis.

Upper limb rehabilitation robot is a relatively new technology, but its effectiveness remains debatable due to the inconsistent results of clinical trials. This article intends to assess how upper limb rehabilitation robots help the functional recovery of stroke patients. PubMed, Embase, Cochrane Library, and Web of Science databases were searched for eligible studies to explore the effect of upper limb rehabilitation robots on upper limb motor function, muscle tone, and daily living activities. Eighteen trials with 573 stroke patients met the inclusion criteria. The results showed that compared to conventional rehabilitation training, patients who received upper limb robotic therapy (RT) had significantly improved Fugl-Meyer Upper Extremity Motor Assessment (FMA-UE) scores (weighted mean differences [WMD]: 5.27, 95% confidence intervals [CI]: 3.36, 7.17), Action Research Arm Test (ARAT) scores (WMD: 4.07, 95% CI: -4.14, 12.28), Modified Barthel Index (MBI) scores (WMD: 9.55, 95% CI: 6.37, 12.73), and modified Ashworth Scale (MAS) scores (WMD: -0.28, 95% CI: -0.50, 0.06), with no significant heterogeneity. Upper limb robot-assisted training is superior to conventional training in terms of improving upper limb motor impairment, ability to perform daily living activities, and muscle tone recovery, which supports the application of robots in clinical practice.

The impact of robots on unemployment duration: Evidence from the Chinese general social survey

The issue of the impact of robot applications on unemployment duration remains relatively unexplored. Using individual-level data from the Chinese General Social Survey (CGSS), we shed new light on the effects of robots on unemployment likelihood and duration. Major findings include that: (1) robots prolong the duration of unemployment, particularly for workers in routine occupations compared to those in non-routine occupations. This phenomenon can be understood as a form of structural unemployment; (2) workers with low skills, low economic and occupational status, and parenting responsibilities suffer more from the robot shock. In particular, robots adversely affect women's careers, and traditional perceptions amplify this effect to dampen their willingness and efforts to find job searching, resulting in longer periods of unemployment. These heterogeneous impacts of robots on unemployment duration highlight the need for greater support and policy interventions for vulnerable groups; (3) access to information from digital channels plays a pivotal role in alleviating the adverse impacts of robots on vulnerable groups. Reducing information asymmetry and nurturing job search capabilities help the vulnerable better adapt to evolving labor market conditions, thereby mitigating the negative consequences of robots.

Exploring the Implementation Methods of AI-Driven Robots in Media Interaction Experience Design

The purpose of this study is to deeply explore the innovative implementation methods of artificial intelligence (AI)-driven robots in media interactive experience design. Firstly, this paper expounds how AI-driven robot technology can provide users with a more natural and intelligent interactive experience through natural language processing (NLP), speech recognition, computer vision and other technologies, thus enhancing users' sense of participation and immersion. In order to realize the efficient application of AI-driven robot in media interaction, this study proposes a series of implementation methods, including improving the accuracy and personalization of robot interaction by using NLP and deep learning algorithm; Identify user expressions and gestures through computer vision technology to enhance the naturalness of interaction; Multi-modal interactive technology is used to integrate multi-sensory channel information to provide comprehensive interactive experience; Use deep learning technology to train the robot's ability to perceive and understand users' needs, and introduce emotion analysis technology to realize more humanized service; By constructing user portraits, we design personalized interaction schemes that adapt to different scenarios and users. In the experimental part, three different scenes, library, shopping mall and museum, are selected to verify the effectiveness of the design scheme. The results show that the AI-driven robot significantly improves the user's satisfaction and emotional experience under the personalized interaction scheme.

A multimodal educational robots driven via dynamic attention.

With the development of artificial intelligence and robotics technology, the application of educational robots in teaching is becoming increasingly popular. However, effectively evaluating and optimizing multimodal educational robots remains a challenge. This study introduces Res-ALBEF, a multimodal educational robot framework driven by dynamic attention. Res-ALBEF enhances the ALBEF (Align Before Fuse) method by incorporating residual connections to align visual and textual data more effectively before fusion. In addition, the model integrates a VGG19-based convolutional network for image feature extraction and utilizes a dynamic attention mechanism to dynamically focus on relevant parts of multimodal inputs. Our model was trained using a diverse dataset consisting of 50,000 multimodal educational instances, covering a variety of subjects and instructional content. The evaluation on an independent validation set of 10,000 samples demonstrated significant performance improvements: the model achieved an overall accuracy of 97.38% in educational content recognition. These results highlight the model's ability to improve alignment and fusion of multimodal information, making it a robust solution for multimodal educational robots.

Ro2En: Robust Neural Environment Encoder for Domain Generalization of Fast Motion Planning

This paper discusses a new issue named domain generalization of fast motion planning in 3D environments, which benefits agility-required robot applications such as autonomous driving and uncrewed aerial vehicle obstacle avoidance flight. The existing work shows that conventional spatial search-based planning algorithms cannot meet the real-time requirement due to high time costs. The end-to-end neural network-based methods achieve an excellent balance between performance and planning speed in the seen environments, but are hard to transfer to new scenarios. To overcome this limitation, we propose a novel Robust Environment Encoder (Ro2En) approach to domain generalization of fast motion planning. Specifically, by demonstrating the reconstructed environment, we find that the previous environment encoder cannot encode the volume information properly, i.e., a volume collapse ensues, which leads to noisy environment modeling. Inspired by this observation, a dual-task auto-encoder is developed. It can not only reconstruct the point cloud of the obstacles, but also align their geometric centers. Experiment results showed that in the new scenarios, Ro2En outperformed previous state-of-the-art conventional and neural alternatives with a much smaller performance variation.

Real-time crop row detection using computer vision- application in agricultural robots.

The goal of achieving autonomous navigation for agricultural robots poses significant challenges, mostly arising from the substantial natural variations in crop row images as a result of weather conditions and the growth stages of crops. The processing of the detection algorithm also must be significantly low for real-time applications. In order to address the aforementioned requirements, we propose a crop row detection algorithm that has the following features: Firstly, a projective transformation is applied to transform the camera view and a color-based segmentation is employed to distinguish crop and weed from the background. Secondly, a clustering algorithm is used to differentiate between the crop and weed pixels. Lastly, a robust line-fitting approach is implemented to detect crop rows. The proposed algorithm is evaluated throughout a diverse range of scenarios, and its efficacy is assessed in comparison to four distinct existing solutions. The algorithm achieves an overall intersection over union (IOU) of 0.73 and exhibits robustness in challenging scenarios with high weed growth. The experiments conducted on real-time video featuring challenging scenarios show that our proposed algorithm exhibits a detection accuracy of over 90% and is a viable option for real-time implementation. With the high accuracy and low inference time, the proposed methodology offers a viable solution for autonomous navigation of agricultural robots in a crop field without damaging the crop and thus can serve as a foundation for future research.

Ethical Reflections on the Application of Medical Robots in Healthcare

With the development and utilization of medical robots, more and more members of the public have begun to pay attention to the risks of practicing medical robots and have expressed concerns about their application. In order to deeply study the ethical risks of medical robots applied in health care, this study chooses the literature research method to reflect on the moral and ethical issues involved in medical robots. The study found that current medical robots have many application scenarios, such as: surgery, rehabilitation care, assisted work and telemedicine. These application scenarios of medical robots may bring ethical risks such as attribution of medical responsibility, doctor-patient relationship, and data algorithms. Intensively, the study points out that inadequate laws, immature values, and technological deficiencies are the most significant factors leading to the aforementioned risks. Thus, adequate attention should be paid to the medical career, the intelligent technology of robots should be improved, and the relevant laws and regulations should be actively improved. This study realistically reflects the current situation and risks of medical robot application, and through in-depth reflection, provides inspiration for robots to better serve the medical cause.

Application of Path Planning and Tracking Control Technology in Mower Robots

Path planning and tracking is the most basic technology for mowing robots, among which the performance of algorithms has a great impact on their intelligence and efficiency. Based on the research of relevant references on mower robots, it mainly focuses on complete coverage path planning, path tracking control, and obstacle avoidance path planning. In complete coverage path planning, three methods were introduced, including simple complete coverage planning, optimal complete coverage planning, and hybrid complete coverage planning. In the path tracking control section, the control methods are divided into three types based on whether the control method depends on the robot model and the type of model, namely model free control method, kinematic model-based control method, and dynamic model-based control method. In obstacle avoidance path planning, we introduce the environment detection device and obstacle avoidance planning algorithm. Then the relevant research papers are analyzed in classification, comparing the research and validation methods adopted by the researchers in the form of charts. Finally, we pointed out the limitations of path planning technology in the application of mower robots. Meanwhile, future development trends are predicted.

Robots in Public Libraries: An Empirical Analysis of Current Applications and Future Opportunities

ABSTRACT The paper investigated the current application of robots in public libraries with specific consideration of its future opportunities. Three (3) objectives guided the conduct of the study. The study employed a qualitative research approach. The population for the study comprised librarians who have been certified by the Librarian Registration Council of Nigeria (LRCN) and worked at public library boards. Thematic analysis and content analysis techniques were adopted for this study. The study found that robots bring various advantages, including increased operational efficiency and streamlined access to information, as well as interactive educational opportunities and heightened user involvement. The findings indicate that embracing robotic technology enables public libraries to establish more accessible, dynamic, and user-focused environments, fostering an atmosphere of innovation and technological progress within the realm of information services. It could be concluded that the integration of robots in public libraries plays a vital role in modernizing and improving library services to meet the evolving demands of library users and communities. However, library stakeholders must address potential obstacles, including financial limitations, technological preparedness, and user acceptance. Prioritizing the training of staff, fostering community involvement, and establishing clear policy frameworks enables public libraries to effectively navigate the challenges related to incorporating robotics, ensuring a smooth transition toward a technologically advanced and user-focused library environment.

Engineering the Future: Robotics in the Automotive Industry Explained

The study provides an overview of the potential applications of industrial robots in the automobile sector, which is now the market's most significant client. An overview of the use of robots in global industry is provided in the first section of the article, which also discusses the state of industrial robot utilization. The most popular uses of robots, particularly in the automotive sector, are covered later, along with developments and outlooks for the field's future. The essay concluded with a specific project overview regarding robotized screw tightening on the car seat production line, which served as a model task from actual industrial practice.The many uses of robots in the automobile industry are examined in this review, including material handling, welding, painting, assembly line automation, and quality control. It emphasizes how collaborative robots (cobots) enhance human-robot interaction and how advances in machine learning and artificial intelligence maximize robotic performance. Keywords: Industrial robot; robotics in automotive; production of passenger cars; transport and production; automated assembly line

A novel mobile robot with origami wheels designed for navigating sandy terrains

Abstract Sand robots play a vital role as mobile tools for human exploration of desert regions, facilitating resource transportation and exploration. However, desert areas primarily consist of beaches or dunes, resulting in a highly diverse and complex terrain environment that demands enhanced adaptability from sandy mobile robots. Traditional wheeled robots currently face challenges such as skidding, limited climbing ability, and inadequate obstacle avoidance capabilities in sandy environments. To address these issues and enable effective adaptation to the intricate sand environment, we propose a novel sandy mobile robot equipped with Kresling origami wheels. The origami wheel can dynamically adjust its width and morphology through Kresling origami folding. Experimental tests were conducted to illustrate the impact of width variation on the robot’s mobility velocity, propulsive force, climbing performance, and carrying capacity. The self-folding malleability of the origami wheel empowers the robot to efficiently accomplish diverse tasks, including swift movement on flat sand surfaces, seamless crossing of narrow channels, and intelligent obstacle avoidance. By successfully completing these multimodal tasks while adapting to varying requirements, our robot demonstrates promising prospects for practical applications of mobile robots equipped with origami wheels – paving the way for wider adaptation and utilization of sand mobile robots.

Retraction notice: Application and use of telepresence robots in libraries and information center services: prospect and challenges

Retraction notice: Application and use of telepresence robots in libraries and information center services: prospect and challenges