Small Robot Research Articles

How to arrange the robotic environment? Leveraging experience in both motion planning and environment optimization

This study presents an experience-based hierarchical-structure optimization algorithm to address the robotic system environment design problem, which combines motion planning and environment arrangement problems together. The motion planning problem, which could be defined as a multiple-degree-of-freedom (m-DOF) problem, together with the environment arrangement problem, which could be defined as a free DOF problem, is a high-dimensional optimization problem. Therefore, the hierarchical structure was established, with the higher layer solving the environment arrangement problem and lower layer solving the problem of motion planning. Previously planned trajectories and past results for this design problem were first constructed as datasets; however, they cannot be seen as optimal. Therefore, this study proposed an experience-reuse manner, which selected the most “useful” experience from the datasets and reused it to query new problems, optimize the results in the datasets, and provide better environment arrangement with shorter path lengths within the same time. Therefore, a hierarchical structural caseGA-ERTC algorithm was proposed. In the higher layer, a novel approach employing the case-injected genetic algorithm (GA) was implemented to tackle optimization challenges in robot environment design, leveraging experiential insights. Performance indices in the arrangement of the robot system’s environment were determined by the robotic arm’s motion and path length calculated using an experience-driven random tree (ERT) algorithm. Moreover, the effectiveness of the proposed method is illustrated with the 12.59% decrease in path lengths by solving different settings of hard problems and 5.05% decrease in easy problems compared with other state-of-the-art methods in three small robots.

Scalable and efficient fabrication of surface microstructures using a small wheeled robot with a vibration-cutting tool

Bioinspired microstructure emerges as a powerful technique to enhance the surface functionalities and properties in a seizes of breakthrough areas. However, its application is limited by the scalability of fabrication methods. This study introduces a scalable fabrication technique utilizing a small wheeled robot designed to operate on a workpiece surface. Due to its unique three-point-support design, the robot maintains a stable cutting depth and exhibits high adaptability to large-scale workpieces. Motion stability is calibrated using a laser displacement sensor, achieving a maximum velocity of approximately 3.7 mm/s. Finally, the robot successfully produces microstructures with a height of 8 μm on aluminum workpieces, demonstrating its promising capacity.

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

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.

Design and Implementation of Small Modular Amphibious Robot System

Various marine engineering facilities have been eroded by marine organisms and wind waves for a long time, resulting in different types of damage to the surface of marine engineering facilities, such as the pile legs of offshore platforms. Therefore, in order to carry out safety inspections and other work on marine engineering facilities, a small amphibious robot structure system and a set of control systems adapted to it are independently developed. Various problems such as the modular design of the structure, composite motion mode, adsorption stability, wall adaptability of the crawling mode, and flaw localization have been solved by means of three-dimensional modeling, mechanical analysis, simulation, and electronic design. At the same time, a set of control systems including hardware and software is developed for the amphibious robot. In order to improve the stability and efficiency of the amphibious robot working underwater, a sliding mode control algorithm based on the exponential reaching law and saturation function is designed. For the fixed depth and fixed heading control functions, the sliding mode control algorithm and the PID control algorithm are simulated and compared. Finally, several types of experiments are carried out for the amphibious robot. The simulation and experimental results show that all the functions of the amphibious robot meet work requirements, such as the motion performance of the composite motion mode. Compared with the PID control algorithm, the sliding mode control algorithm has a faster response speed and better stability, which is conducive to the efficient and stable work of the amphibious robot underwater.

Portable Machine Tools by Small Piezoelectric Robots for Scalable and Waviness‐Adaptive Fabrication of Surface Microstructures

Surface functional microstructures exhibit extensive application requirements in an array of breakthrough areas. One critical problem that restricts their industrial application is the lack of scalable fabrication techniques due to the limitation of conventional machine tools. This study proposes a scalable surface texturing technique using a portable small (30 × 19 × 22 mm) three‐leg robot that walks and works on the workpiece surface. Due to the elliptical tool vibration, microgrooves can be created on the workpiece surface periodically; meanwhile, the machining force drives the robot to walk forward. Surface texturing experiments are conducted on aluminum and copper workpieces to explore the machining performance of the small robot. The robot can reach a maximum moving velocity of 6.3 mm s−1 and can produce microstructures with a spacing of 4–14 μm on workpiece surfaces. Owing to its unique working principle, the small robot can maintain a constant depth of cut, demonstrating its capacity to adapt to the surface waviness of the workpiece. Finally, the motion straightness of the robot is greatly improved by combining it with the auxiliary track, and multiline microstructures are obtained. In short, the developed small robot presents a promising solution to the challenge of scalable surface texturing.

Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras

The aim of this study was to estimate field-grown tomato yield (weight) and quantity of tomatoes using a self-developed robot and digital single lens reflex (DSLR) camera pictures. The authors suggest a new approach to predicting tomato yield that is based on images taken in the field, 3D scanning, and shape. Field pictures were used for tomato segmentation to determine the ripeness of the crop. A convolution neural network (CNN) model using TensorFlow library was devised for the segmentation of tomato berries along with a small robot, which had a 59.3 % F1 score. To enhance the accurate tomato crop model and to estimate the yield later, point cloud imaging was applied using a Ciclops 3D scanner. The best fitting sphere model was generated using the 3D model. The most optimal model was the 3D model, which gave the best representation and provided the weight of the tomatoes with a relative error of 21.90 % and a standard deviation of 17.9665 %. The results indicate a consistent object-based classification of the tomato crop above the plant/row level with an accuracy of 55.33 %, which is better than in-row sampling (images taken by the robot). By comparing the measured and estimated yield, the average difference for DSLR camera images was more favorable at 3.42 kg.

High Performance MXene/MnCo2O4 Supercapacitor Device for Powering Small Robotics.

The development of advanced energy storage devices is critical for various applications including robotics and portable electronics. The energy storage field faces significant challenges in designing devices that can operate effectively for extended periods while maintaining exceptional electrochemical performance. Supercapacitors, which bridge the gap between batteries and conventional capacitors, offer a promising solution due to their high power density and rapid charge-discharge capabilities. This study focuses on the fabrication and evaluation of a MXene/MnCo2O4 nanocomposite supercapacitor electrode using a simple and cost-effective electrodeposition method on a copper substrate. The MXene/MnCo2O4 nanocomposite exhibits superior electrochemical properties, including a specific capacitance of 668 F g-1, high energy density (35 Wh kg-1), and excellent cycling stability (94.6% retention over 5000 cycles). The combination of MXene and MnCo2O4 enhances the redox activity, electronic conductivity, and structural integrity of the electrode. An asymmetric supercapacitor device, incorporating MXene/MnCo2O4 as the positive electrode and Bi2O3 as the negative electrode, demonstrates remarkable performance in powering small robotics and small electronics. This work underscores the potential of MXene-based nanocomposites for high-performance supercapacitor applications, paving the way for future advancements in energy storage technologies.

Intelligent Surface Recognition for Autonomous Tractors Using Ensemble Learning with BNO055 IMU Sensor Data

This study aims to enhance the navigation capabilities of autonomous tractors by predicting the surface type they are traversing using data collected from BNO055 Inertial Measurement Units (IMU sensors). IMU sensor data were collected from a small mobile robot driven over seven different floor surfaces within a university environment, including tile, carpet, grass, gravel, asphalt, concrete, and sand. Several machine learning models, including Logistic Regression, K-Neighbors, SVC, Decision Tree, Random Forest, Gradient Boosting, AdaBoost, and XGBoost, were trained and evaluated to predict the surface type based on the sensor data. The results indicate that Random Forest and XGBoost achieved the highest accuracy, with scores of 98.5% and 98.7% in K-Fold Cross-Validation, respectively, and 98.8% and 98.6% in an 80/20 Random State split. These findings demonstrate that ensemble methods are highly effective for this classification task. Accurately identifying surface types can prevent operational errors and improve the overall efficiency of autonomous systems. Integrating these models into autonomous tractor systems can significantly enhance adaptability and reliability across various terrains, ensuring safer and more efficient operations.

Buoyancy and Propulsion Mechanisms for Stable Movement in Snow Field

For small-sized mobile machines, moving on snow without sinking is challenging. Snowmobiles are often used to move on snow. However, in smaller-sized machines, the skis attached to the machine become small, so small snow bumps or soft powdered snow quickly cause the entire machine to be buried under the snow. Therefore, it is necessary for small robots moving on snow to give appropriate driving mechanisms for producing propulsive force and snow-floating force. To this end, we propose new driving mechanisms, a “passive wing wheel” and a “spiral screw,” for small mobility services that move on snow without sinking or getting stuck. The passive wing wheel has transformable wing-like paddles, which extend to behave like animal feet and shrink to form a wheel if necessary. The spiral screw is designed to produce propulsive force by pushing snow particles with the screw. Additionally, by combining two sets of screws having opposite threads, they gather snow underneath the body attached to them, which causes floating force. This report also proposes ways to prepare pseudo-snow, which resembles natural snow in hardness, viscosity, and property transformation due to deformation. We conducted experiments to measure the performance of the proposed design in both the pseudo-snow and natural snow. From experiments, we confirmed that the mechanism performs well in terms of propulsion and floating on snow.

Analysis of the Pet Companion Robot Market

Pet robot is a kind of intelligent device with artificial intelligence and mechanical technology. These robots provide a solution to the challenges of balancing work responsibilities and caring for pets, while also enhancing the interaction between owners and pets to ensure the health of pets. The pet robot market is a new technology market, through the in-depth study of the pet robot market, it can fill the research gap in this field and provide new research opportunities for the academic circle. Through the research methods of questionnaire survey and literature review, we compared the global market strategies of large, small and medium-sized technology pet robot companies, combined with the quantitative literature review and questionnaire quantitative analysis, and drew the conclusion that the pet robot market has great potential, but the entry barrier is high, and the differentiation strategy is needed.

Analysis of the Pet Companion Robot Market

Pet robot is a kind of intelligent device with artificial intelligence and mechanical technology. These robots provide a solution to the challenges of balancing work responsibilities and caring for pets, while also enhancing the interaction between owners and pets to ensure the health of pets. The pet robot market is a new technology market, through the in-depth study of the pet robot market, it can fill the research gap in this field and provide new research opportunities for the academic circle. Through the research methods of questionnaire survey and literature review, we compared the global market strategies of large, small and medium-sized technology pet robot companies, combined with the quantitative literature review and questionnaire quantitative analysis, and drew the conclusion that the pet robot market has great potential, but the entry barrier is high, and the differentiation strategy is needed.

A study on design and moving behavior of meal partner robots that can perform eating behavior expression

Dining with people improves our lives and brings a lot of benefits. Nonetheless, many people are compelled to eat by themselves due to the current social situation. We believe that robots can be good meal partners. In this paper, we describe the developed meal partner robots called Mamoru'21 and Mamoru'22. The design of these robots is inherited from a robot for watching over elderly people. Based on previous research that robot's eating behavior expression can improve the mealtime experience, they can perform motions that mimic eating and present food images by monitors. In the first experiment, we confirmed the developed robot could improve the co-eating experience compared to a conventional small humanoid robot, and investigated the keywords for preferable hardware design, such as ‘smaller than a child.’ In the second experiment, we studied the effects of the robot's moving around during mealtime. As a result, no statistically significant negative effects of robot movement during meals were observed in the developed robot's capability. Though this study has some limitations such as shorter experimentation time compared to regular meals, it contributes some insights and knowledge into the behavior and design of meal partner robots.

3D printing of flexible piezoelectric composite with integrated sensing and actuation applications

3D printing of flexible piezoelectric composites (3D-FPCs) is increasingly attracting the attention due to its unique advantage for customized smart applications. However, current research mainly focuses on the 0–3 piezoelectric composites, in which the piezoelectric ceramics are embedded in polymer matrix in the form of particles. The poor connectivity between particles much reduces the conduction of strain and charge in the composites, seriously limiting its application in actuation. In this work, a continuous lead zirconate titanate (PZT) double-layer ceramic scaffold was prepared by 3D printing and assembled with epoxy resin and interdigital electrodes together to manufacture a multifunctional device. The 3D-FPCs exhibit a free strain of 1830 ​ppm in actuating and are able to actuate a stainless-steel cantilever beam to produce a tip displacement of 5.71 ​mm. Additionally, the devices exhibit a sensitivity of 26.81V/g in sensing applications. Furthermore, 3D-FPCs are demonstrated as actuators for mobile small robots and wearable sensors for sensing joint activities.

Marangoni Droplets of Dextran in PEG Solution and Its Motile Change Due to Coil-Globule Transition of Coexisting DNA.

Motile droplets using Marangoni convection are attracting attention for their potential as cell-mimicking small robots. However, the motion of droplets relative to the internal and external environments that generate Marangoni convection has not been quantitatively described. In this study, we used an aqueous two-phase system [poly(ethylene glycol) (PEG) and dextran] in an elongated chamber to generate motile dextran droplets in a constant PEG concentration gradient. We demonstrated that dextran droplets move by Marangoni convection, resulting from the PEG concentration gradient and the active transport of PEG and dextran into and out of the motile dextran droplet. Furthermore, by spontaneously incorporating long DNA into the dextran droplets, we achieved cell-like motility changes controlled by coexisting environment-sensing molecules. The DNA changes its position within the droplet and motile speed in response to external conditions. In the presence of Mg2+, the coil-globule transition of DNA inside the droplet accelerates the motile speed due to the decrease in the droplet's dynamic viscosity. Globule DNA condenses at the rear part of the droplet along the convection, while coil DNA moves away from the droplet's central axis, separating the dipole convections. These results provide a blueprint for designing autonomous small robots using phase-separated droplets, which change the mobility and molecular distribution within the droplet in reaction with the environment. It will also open unexplored areas of self-assembly mechanisms through phase separation under convections, such as intracellular phase separation.

Smart insect-computer hybrid robots empowered with enhanced obstacle avoidance capabilities using onboard monocular camera

Insect-computer hybrid robots are receiving increasing attention as a potential alternative to small artificial robots due to their superior locomotion capabilities and low manufacturing costs. Controlling insect-computer hybrid robots to travel through terrain littered with complex obstacles of various shapes and sizes is still challenging. While insects can inherently deal with certain obstacles by using their antennae to detect and avoid obstacles, this ability is limited and can be interfered with by control signals when performing navigation tasks, ultimately leading to the robot being trapped in a specific place and having difficulty escaping. Hybrid robots need to add additional sensors to provide accurate perception and early warning of the external environment to avoid obstacles before getting trapped, ensuring smooth navigation tasks in rough terrain. However, due to insects’ tiny size and limited load capacity, hybrid robots are very limited in the sensors they can carry. A monocular camera is suitable for insect-computer hybrid robots because of its small size, low power consumption, and robust information acquisition capabilities. This paper proposes a navigation algorithm with an integrated obstacle avoidance module using a monocular camera for the insect-computer hybrid robot. The monocular cameras equipped with a monocular depth estimation algorithm based on deep learning can produce depth maps of environmental obstacles. The navigation algorithm generates control commands that can drive the hybrid robot away from obstacles according to the distribution of obstacle distances in the depth map. To ensure the performance of the monocular depth estimation model when applied to insect-computer hybrid robotics scenarios, we collected the first dataset from the viewpoint of a small robot for model training. In addition, we propose a simple but effective depth map processing method to obtain obstacle avoidance commands based on the weighted sum method. The success rate of the navigation experiment is significantly improved from 6.7% to 73.3%. Experimental results show that our navigation algorithm can detect obstacles in advance and guide the hybrid robots to avoid them before they get trapped.

Kinematic Analysis of a Wheeled-Leg Small Pipeline Robot Turning in Curved Pipes

A wheeled-leg pipeline robot suitable for operation in small pipes is proposed to address the challenges of detecting the condition of pipelines, such as solution corrosion and crack defects, which cannot be conducted externally due to the pre-buried pipe system embedded in other structures. Inspired by existing pipeline robots, the proposed robot employs a mechanical structure with six wheeled legs arranged in an alternating pattern. To analyze the motion state of the pipeline robot turning in curved pipes, kinematic analysis based on geometry is conducted to figure out the kinematic characteristics of the robot navigating in curved pipes. The relationship between the motion trajectories of each contact wheel and the posture angle of the robot in the pipeline is the focal point. Additionally, a turning method preventing wheel slippage is proposed specifically for this type of robot. Finally, an experiment with the pipeline robot navigating in the curved pipeline is implemented and demonstrates successful passing through curved pipes with an inner diameter of 120 mm as well as a turning radius of 240 mm, with the effectiveness of the kinematic analysis validated.

Research on the operation and quality control of small rock hole shotcrete robot

A small rock shotcrete robot is applied in the deep tunnel dynamic disaster physical simulation system in order to simulate the final operation process of the tunnel project. The robot’s spraying operation and control include many kind of factors. In this paper, the main parameters affecting the spraying operation are analyzed by establishing the spraying model and coating growth model. For matching reasonably the spraying parameters, the matching equation of spraying quality and spraying gun parameter model and spraying feed speed has been derived. Based on the matching equation, the spraying gun structure and robot control system are designed, and the spraying distance and spraying gun movement velocity including horizontal and vertical driving have been controlled better. On the basis of theoretical analysis, a small rock hole shotcrete robot prototype has been developed and the spraying experiments have been finished. The experimental results showed that the model and equation established can guided the spraying quality control. With the increase of the injection elevation angle, the length of the long and short axes of the elliptic coating becomes larger, and the average thickness of the coating center is between 2.23 and 2.34 mm, which meets the design index of the injection robot. The rock hole shotcrete robot meet the design requirements.

Autonomous robot vacuum system composed of a cleaner robot and a dust storage robot

In this paper, we address an autonomous robot vacuum system, composed of two robots. Conventional robot vacuum has a small dust bin, and its suction power is low. This low cleaning power has been considered as a defect of a conventional robot vacuum. If we use a large robot vacuum with high cleaning power, then we cannot clear various narrow environments, such as narrow space under a sofa. To resolve this problem, we address an autonomous robot vacuum system composed of a small Cleaner Robot (CR) and a large dust Storage Robot (SR). The CR and the SR are connected using a hose, thus they must maneuver as a pair. The role of the small CR is to clean various environments, such as narrow space under a sofa. The CR is small, thus it cannot contain a large motor for increasing its cleaning power. The dust sucked by the CR is transmitted to the SR through the hose. The SR is large, hence it can have a large motor for increasing its cleaning power compared to a conventional robot vacuum. To the best of our knowledge, our paper is novel in addressing an autonomous robot vacuum system composed of a CR and a SR. Our paper is unique in addressing the path plan of these two connected robots, so that the entire open workspace can be cleaned by the CR as fast as possible. Under MATLAB simulations, we demonstrate the effectiveness of path planning for our autonomous robot vacuum system. We show that the proposed tethered robots improve the cleaning efficiency, compared to the case where a single large robot vacuum is applied.

Experimental and numerical study of a second-order transition in the behavior of confined self-propelled particles.

In this paper, we conduct experimental investigations on the behavior of confined self-propelled particles within a circular arena, employing small commercial robots capable of locomotion, communication, and information processing. These robots execute circular trajectories, which can be clockwise or counterclockwise, based on two internal states. Using a majority-based stochastic decision algorithm, each robot can reverse its direction based on the states of two neighboring robots. By manipulating a control parameter governing the interaction, the system exhibits a transition from a state where all robots rotate randomly to one where they rotate uniformly in the same direction. Moreover, this transition significantly impacts the trajectories of the robots. To extend our findings to larger systems, we introduce a mathematical model enabling characterization of the order transition type and the resulting trajectories. Our results reveal a second-order transition from active Brownian to chiral motion.

Global challenges and the ‘farm to fork’ strategies of the European Green Deal: Blessing or curse

AbstractThe article evaluates how well the goals of the European Green Deal are justified, especially considering the risks to energy and food security arising from the conflict between Russia and Ukraine. We agree with the objectives of the European Green Agreement as a whole, but whether some of the objectives which feature in the EASAC study can be achieved by 2030 is questionable, and the description of the tools necessary to achieve the objectives is incomplete. Among other things, there is hardly any mention of the role played by precision farming with digitalization, which is a revolutionary change from an ecological and economic point of view, in reducing the use of synthetic inputs, in regenerating the original state of the soil, in reducing GHG emissions, thus in increasing biodiversity, and at the same time in intensifying production, and finally in expanding the application of biotechnology. We examine these areas in our analysis. Some of the objectives of the EASAC study to be achieved by 2030 are subject to debate, and the description of the information and communication conditions necessary to achieve the objectives is incomplete. The IoT (Internet of Things) responds to global and local challenges: it integrates the precision technologies, WSNs (Wireless Sensor Networks), artificial intelligence, mobile field (Smart Small Robots) and remote data loggers (UAVs: Unmanned Air Vehicles and satellites), Big Data, and cloud computing. Consequently, decision support is increasingly developing into unmanned decision making. IoT (Internet of Things) is the basis of “Farm to Fork” and “Lab to Field” monitoring approaches.This article evaluates the implementation of European Green Agreement objectives in light of energy and food security risks arising from the Russia-Ukraine conflict. While overall support for the agreement exists, the feasibility of certain EASAC study objectives by 2030 is called into question due to insufficient tools specifications. Notably absent is the emphasis on precision farming with digitalization, which is a transformative ecological and economic practice. Our analyses look into its function in reducing synthetic inputs, soil regeneration, GHG emission reduction, biodiversity enhancement, production intensification, and biotechnology development. Debates surround EASAC study objectives for 2030, despite limited information and communication restrictions. The Internet of Things (IoT) arises as a solution, combining precision technology, WSNs (wireless sensor networks), AI (artificial intelligence), smart small robots, UAVs (unmanned aerial vehicles), satellites, big data, and cloud computing. As a result, decision support turns toward unmanned decision-making, with IoT laying the groundwork for “Farm to Fork” and “Lab to Field” monitoring systems.