Robotics Research Research Articles

Limb coordination: Coming together to bounce along

Experimental, modeling, and robotic research shows that switching of sea stars from crawling to bouncing gaits does not require centralized neural control. Bouncing can instead arise cooperatively, with synchronization of sea star tube feet occurring by locally acting mechanisms alone.

Soft Robotics: A Route to Equality, Diversity, and Inclusivity in Robotics.

Robotics is entering our daily lives. The discipline is increasingly crucial in fields such as agriculture, medicine, and rescue operations, impacting our food, health, and planet. At the same time, it is becoming evident that robotic research must embrace and reflect the diversity of human society to address these broad challenges effectively. In recent years, gender inclusivity has received increasing attention, but it still remains a distant goal. In addition, awareness is rising around other dimensions of diversity, including nationality, religion, and politics. Unfortunately, despite the efforts, empirical evidence shows that the field has still a long way to go before achieving a sufficient level of equality, diversity, and inclusion across these spectra. This study focuses on the soft robotics community-a growing and relatively recent subfield-and it outlines the present state of equality and diversity panorama in this discipline. The article argues that its high interdisciplinary and accessibility make it a particularly welcoming branch of robotics. We discuss the elements that make this subdiscipline an example for the broader robotic field. At the same time, we recognize that the field should still improve in several ways and become more inclusive and diverse. We propose concrete actions that we believe will contribute to achieving this goal, and provide metrics to monitor its evolution.

On Emergent Limits to Knowledge—Or, How to Trust the Robot Researchers: A Pocket Guide

On Emergent Limits to Knowledge—Or, How to Trust the Robot Researchers: A Pocket Guide

Target tracking techniques for multi-robot systems: Review on the state-of-the-art

The field of target tracking has long been a focal point in robotics research, gaining particular prominence in the realm of multi-robot systems. Target tracking has extensive applications in diverse areas such as surveillance, search and rescue operations, and environmental detection. This paper presents an exhaustive review of the latest target tracking methodologies employed in multi-robot systems, with an emphasis on scenarios featuring both abundant and limited information availability. The review particularly addresses the challenges posed by conditions including target occlusion (partial or total), uncertainties in robots positional data, and limitations in sensory and communicative functions. This scholarly piece synthesizes literature sourced from IEEE and Springer publications, spanning the period from 2019 to 2023. This temporal scope ensures a focus on contemporary and pertinent research outcomes. The findings of this paper indicate a significant evolution in the sophistication of target tracking techniques, particularly in complex operational scenarios. These advancements signify a notable maturation in the capabilities of multi-robot systems to efficiently handle intricate and varied tasks.

How does the status of errant robot affect our desire for contact? – The moderating effect of team interdependence

Technological breakthroughs such as artificial intelligence and sensors make human-robot collaboration a reality. Robots with highly reliable, specialised skills gain informal status in collaborative teams, but factors such as unstructured work environments and task requirements make robot error inevitable. So how do status differences of errant robots affect the desire for contact, and do team characteristics also have an impact? This paper describes an intergroup experiment using the Experimental Vignette Method (EVM), based on the Expectation Violation Theory, 214 subjects were invited to test the following hypotheses: (1) Errant robot status has an influence on employees' desire for contact and support for robotics research through negative emotions; (2) Team interdependence is a boundary condition for the effect of errant robot status on negative emotions. This paper contributes to the literature on employee reactions to robot errors in human-robot collaboration and provides suggestions for robot status design.

Development of metaheuristic algorithms for efficient path planning of autonomous mobile robots in indoor environments

The application of efficient path planning algorithms for two-wheeled Autonomous Mobile Robots (AMRs) in static environments with obstacles is a significant challenge in robotics research. Existing methods, such as the A star (A*) algorithm utilized in Robot Operating System 2 (ROS2), can provide optimal paths but may have high computational complexity in intricate environments. This study explores the potential of three metaheuristic algorithms - Improved Particle Swarm Optimization (IPSO), Improved Grey Wolf Optimizer (IGWO), and Artificial Bee Colony (ABC) - for planning efficient and smooth paths in static environments. These algorithms are selected due to their ability to efficiently find near-optimal solutions and avoid local minima. In this study, the researchers designed and built a two-wheeled AMR using a Raspberry Pi 4 microcontroller as the main processing unit, working in conjunction with an Arduino Mega for controlling the DC motor drive through an MDD10A motor driver circuit. The robot is equipped with an RPLiDAR A1 sensor to read 360-degree distance values for mapping and obstacle avoidance. The experimental results clearly indicate that the metaheuristic algorithms, especially ABC, can calculate paths up to 7% shorter than A* while requiring only one-tenth of the time. Moreover, ABC demonstrates superior motion smoothness when applied to the actual two-wheeled robot in static environments. This work represents a significant step in developing algorithms for two-wheeled robots that are ready to support real-world operations in industries, logistics, healthcare, or various service sectors, which can help increase efficiency and reduce operating costs in the future.

Recent Advances in Robotics and Intelligent Robots Applications

Robotics research has a unique allure for both academia and the industry due to its potential for groundbreaking innovation and real-world applications [...]

Development of an IoT based 3D printed Mobile Robot Platform for training of Mechatronics Engineering Students

The advent of the Internet of Things (IoT) has opened up new opportunities in education, particularly in the field of mobile robotics. Mobile robotics is a fast-growing field, and with the increasing demand for skilled robotics engineers, it is essential to provide students with hands-on experience in designing and developing robots. In this regard, an IoT-based 3D printed mobile robot platform has been developed for students training. STEM (Science, Technology, Engineering, and Mathematics) education has been gaining attention as a means to improve science and engineering education. STEM education aims to foster critical thinking, problem-solving skills, creativity, and innovation among students. It involves an educational policy that aims to develop the next generation of skilled professionals by integrating the fields of Science, Technology, Engineering and Mathematics. The goal of this approach is to provide students in mechatronics, who are assigned to the robotics lab during their studies, an up to date knowledge and experience in research and development activities. Thus, this paper aims to provide education that focuses on the acquisition and application of engineering knowledge, including control engineering, mechanical engineering, electrical and electronic engineering, information engineering, among others, with the main focus on mobile robot research.

Structural design and coupling analysis of multimode variable coupling parallel mobile robots

Purpose There is coupling between the branches of mobile parallel robots, similar to traditional parallel mechanisms, but there is currently relatively little research on the coupling problem between the branches of mobile parallel robots. Design/methodology/approach This study optimizes the coupling analysis method of traditional parallel mechanisms, treats the mobile parallel mechanism as a whole, takes the motion of the active pair as input and the overall motion of the mobile parallel mechanism as output and analyzes the input–output characteristics of the mobile parallel mechanism. Moreover, this study applies this theory to a mobile parallel mechanism, designs control logic and finally conducts simulation and physical verification. Findings This study proposes a coupling analysis method suitable for parallel mobile robots and designs the control logic of their active pair based on the results of their coupling analysis. This study designs a multimode variable coupling parallel mobile robot, which can change the coupling of the mechanism by changing its own branch chain structure, so that it can switch between different coupling configurations to meet the different needs brought by different terrains. Originality/value The work presented in this paper propose a method for analyzing the coupling of mobile parallel robots and simplify their control logic by applying coupling theory to the design of mobile parallel robots. This study conducts simulation and physical experiments, thereby filling the gap in the coupling analysis of parallel mobile robots and laying the foundation for the research of uncoupled parallel mobile robots.

Multi-sensor fusion based wheeled robot research on indoor positioning method

In response to the poor positioning performance and errors of the wheeled robot under a single sensor, a combination of wheel odometry dead reckoning, Inertial Measurement Unit (IMU) heading angle information, and map environment information obtained from LiDAR is used for indoor positioning of the wheeled robot. By using data from multiple sensors, errors are reduced and positioning accuracy is improved. The results show that combining the Extended Kalman Filter (EKF), Gmapping algorithm, and Adaptive Monte Carlo Localization (AMCL) reduces the relative error by 8.35 % compared to the single wheel odometry heading calculation method. Compared with the EKF fusion method for dead reckoning and inertial measurement unit heading angle information, the relative error is reduced by 4 %, and there is no cumulative trend in angle error. This effectively addresses the challenge of cumulative errors in indoor positioning within environments that lack base stations, thereby enhancing accuracy and reliability in such specialized conditions.

Self-Perceptional Soft Robotics by a Dielectric Elastomer.

Soft robotics has been a rapidly growing field in recent decades due to its advantages of softness, deformability, and adaptability to various environments. However, the separation of perception and actuation in soft robot research hinders its progress toward compactness and flexibility. To address this limitation, we propose the use of a dielectric elastomer actuator (DEA), which exhibits both an actuation capability and perception stability. Specifically, we developed a DEA array to localize the 3D spatial position of objects. Subsequently, we integrate the actuation and sensing properties of DEA into soft robots to achieve self-perception. We have developed a system that integrates actuation and sensing and have proposed two modes to achieve this integration. Furthermore, we demonstrated the feasibility of this system for soft robots. When the robots detect an obstacle or an approaching object, they can swiftly respond by avoiding or escaping the obstacle. By eliminating the need for separate perception and motion considerations, self-perceptional soft robots can achieve an enhanced response performance and enable applications in a more compact and flexible field.

Bio-inspired mobile robot design and autonomous exploration strategy for underground special space

PurposeTo make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no longer satisfied with enabling robots to build maps by remote control, more needs will focus on the autonomous exploration of unknown areas, which refer to the low light, complex spatial features and a series of unstructured environment, lick underground special space (dark and multiintersection). This study aims to propose a novel robot structure with mapping and autonomous exploration algorithms. The experiment proves the detection ability of the robot.Design/methodology/approachA small bio-inspired mobile robot suitable for underground special space (dark and multiintersection) is designed, and the control system is set up based on STM32 and Jetson Nano. The robot is equipped with double laser sensor and Ackerman chassis structure, which can adapt to the practical requirements of exploration in underground special space. Based on the graph optimization SLAM method, an optimization method for map construction is proposed. The Iterative Closest Point (ICP) algorithm is used to match two frames of laser to recalculate the relative pose of the robot, which improves the sensor utilization rate of the robot in underground space and also increase the synchronous positioning accuracy. Moreover, based on boundary cells and rapidly-exploring random tree (RRT) algorithm, a new Bio-RRT method for robot autonomous exploration is proposed in addition.FindingsAccording to the experimental results, it can be seen that the upgraded SLAM method proposed in this paper achieves better results in map construction. At the same time, the algorithm presents good real-time performance as well as high accuracy and strong maintainability, particularly it can update the map continuously with the passing of time and ensure the positioning accuracy in the process of map updating. The Bio-RRT method fused with the firing excitation mechanism of boundary cells has a more purposeful random tree growth. The number of random tree expansion nodes is less, and the amount of information to be processed is reduced, which leads to the path planning time shorter and the efficiency higher. In addition, the target bias makes the random tree grow directly toward the target point with a certain probability, and the obtained path nodes are basically distributed on or on both sides of the line between the initial point and the target point, which makes the path length shorter and reduces the moving cost of the mobile robot. The final experimental results demonstrate that the proposed upgraded SLAM and Bio-RRT methods can better complete the underground special space exploration task.Originality/valueBased on the background of robot autonomous exploration in underground special space, a new bio-inspired mobile robot structure with mapping and autonomous exploration algorithm is proposed in this paper. The robot structure is constructed, and the perceptual unit, control unit, driving unit and communication unit are described in detail. The robot can satisfy the practical requirements of exploring the underground dark and multiintersection space. Then, the upgraded graph optimization laser SLAM algorithm and interframe matching optimization method are proposed in this paper. The Bio-RRT independent exploration method is finally proposed, which takes shorter time in equally open space and the search strategy for multiintersection space is more efficient. The experimental results demonstrate that the proposed upgrade SLAM and Bio-RRT methods can better complete the underground space exploration task.

A ray-inspired flexible robot fish with stable controllability actuated by photo -responsive composite hydrogels with poly(N-isopropylacrylamide) and multi-walled carbon nanotubes

Drawing inspiration from the movement behaviour of rays in nature, we have successfully developed a ray-inspired flexible robot fish driven by visible light. A composite made of poly(N-isopropylacrylamide) (PNIPAM) and multi-walled carbon nanotubes (MWCNTs) has excellent biocompatibility and photo-responsive deformability. The PNIPAM hydrogel flexible material of the robot fish was prepared by light curing printing technology. Under the control of visible light, the robot fish swims in a straight line at an average speed of about 0.42 mm/s. The photoinduced asymmetric deformation mechanism is used to control the deformation of the fins on both sides of the robot fish, so that the robot fish can turn and realize directional swimming control. These findings have important implications for the development of flexible bionic robots and provide valuable insights for the research of bionic robots driven by visible light.

Application of artificial neural synapses in soft robots

Artificial neural network is considered to be one of the effective ways to enable soft robots to achieve high-performance control due to their significant advantages, such as massively parallel processing and distributed storage of information, adaptivity, and fault tolerance. Artificial neural networks are composed of microelectronic components connected together, of which the most basic units are artificial neural synaptic units, such as atomic switches, memristors, and synaptic transistors. This paper first introduces the research status of soft robots and artificial neural synapses, predicts the demand of soft robots for artificial neural synapses, summarizes the difficulties and problems that may be encountered in the application of artificial neural synapses to soft robots, and finally points out the importance and feasibility of artificial neural synapses in the research and development of soft robots.

Numerical Simulation of Motion Test of Bionic Amphibious Quadruped Robot

Bionic amphibious quadruped robots are a huge leap in robotics, with the ability to navigate various terrains with agility and efficiency. In this study, the researchers utilized numerical simulations of motion tests to assess the locomotion skills of these extraordinary robotic systems. They learned a lot about their functioning and problems by rigorously analyzing performance parameters across various terrains and conditions, such as terrain adaptability, traversal speed, energy efficiency, stability, and manoeuvrability. The results they obtained highlighted the importance of adaptive control algorithms and mechanical designs in maximizing traversal speed and energy economy, especially while negotiating difficult terrains. In addition, the study demonstrated the interdisciplinary character of research in bionic amphibious quadruped robots, drawing on insights from biomechanics, control theory, robotics, and computational modelling. By combining previous research and utilizing computational simulation approaches, they opened the road for the creation of versatile and durable robotic systems capable of navigating difficult terrains and surroundings with precision and efficiency. Future research efforts could focus on improving design and control, investigating novel propulsion mechanisms, adaptive locomotion tactics, and biomimetic control algorithms to improve performance and adaptability. Addressing the challenges identified in the research and seizing opportunities for innovation will drive the development of robotic systems that push the limits of locomotion capabilities and open up new possibilities for applications in exploration, search and rescue, environmental monitoring, and beyond.

Robot obstacle avoidance optimization by A* and DWA fusion algorithm.

The current robot path planning methods only use global or local methods, which is difficult to meet the real-time and integrity requirements, and can not avoid dynamic obstacles. Based on this, this study will use the improved A-star global planning algorithm to design a hybrid robot obstacle avoidance path planning algorithm that integrates sliding window local planning methods to solve related problems. Specifically, A-star is optimized by evaluation function, sub node selection mode and path smoothness, and fuzzy control is introduced to optimize the sliding window algorithm. The study conducted algorithm validation on the TurtleBot3 mobile robot, with data sourced from experimental data from a certain college. The results showed that hybrid algorithm enabled the planned path to effectively navigate around dynamic obstacles and reach the target point accurately. When compared with traditional methods, path length reduced by 9.6%, path planning time decreased by 29% with an approximate 26.7% increase in the average speed of the robot. Compared with the traditional methods, the research algorithm has greatly improved in avoiding dynamic obstacles, path planning efficiency, model adaptability and so on, which has important value for relevant research. It can be seen that the algorithm proposed in the study has performance advantages, demonstrating the effectiveness and advantages of robot path planning, and can provide reference for robot obstacle avoidance optimization. Research can complete tasks for robots in practical environments, which has certain reference value for the research of robots in path planning and the development of path obstacle avoidance planning.

DESIGN AND DEVELOPMENT OF FERTILISER SPRAYING AGRICULTURAL ROBOT

Modern agriculture is ensured by the development and dissemination of agricultural automation and intelligence. The current focus of agricultural robot research is autonomous navigation, which can significantly improve labor productivity while effectively reducing labor requirements. It is the most successful robot in the agricultural field. The main functions of the robot are chassis control, navigation control, and mechanical design for fertilization and spreading. The main theme of robots is to reduce work, workload, burden and stress. Agriculture is an extremely resource- and labor-intensive industry. Therefore, farmers are increasingly turning to technology and automation to address this problem. Future recommendations include making agricultural robots fully autonomous. Key Words: Fertilization, agricultural robots modern agriculture, autonomous navigation.

A decision support system for upper limb rehabilitation robot based on hybrid reasoning with RBR and CBR.

The rehabilitation robot can assist hemiplegic patients to complete the training program effectively, but it only focuses on helping the patient's training process and requires the rehabilitation therapists to manually adjust the training parameters according to the patient's condition. Therefore, there is an urgent need for intelligent training prescription research of rehabilitation robots to promote the clinical applications. This study proposed a decision support system for the training of upper limb rehabilitation robot based on hybrid reasoning with rule-based reasoning (RBR) and case-based reasoning (CBR). The expert knowledge base of this system is established base on 10 professional rehabilitation therapists from three different rehabilitation departments in Shanghai who are enriched with experiences in using desktop-based upper limb rehabilitation robot. The rule-based reasoning is chosen to construct the cycle plan inference model, which develops a 21-day training plan for the patients. The case base consists of historical case data from 54 stroke patients who underwent rehabilitation training with a desktop-based upper limb rehabilitation robot. The case-based reasoning, combined with a Random Forest optimized algorithm, was constructed to adjust the training parameters for the patients in real-time. The system recommended a rehabilitation training program with an average accuracy of 91.5%, an average AUC value of 0.924, an average recall rate of 88.7%, and an average F1 score of 90.1%. The application of this system in rehabilitation robot would be useful for therapists.

Characterising CSCW Research on Human-Robot Collaboration

Human-Robot Collaboration (HRC) is an increasingly prominent topic in CSCW. From telepresence systems through field robots for extreme missions to social robots in homes, HRC is becoming a recurring theme across a broad range of CSCW research. Based on the growing interest, we explore the coupling of the field of CSCW and research on robotics at this critical time. This paper presents a primary and secondary literature review of CSCW proceedings and venues for robotics research. We identified 29 CSCW papers that contribute to the body of HRC research and analyse the foundations on which these papers rely. Then, we identified 138 papers published in robotics outlets that either (1) cite one or more CSCW papers, or (2) use the term CSCW. We discuss how CSCW is currently contributing to HRC research through five research topics: Sociomateriality, teamwork, awareness, embodiment, and communication. The paper contributes by offering three key future pathways for expanding this area of research, outlining questions and gaps that have yet to be explored for (1) expanding the application domains and diversifying robot types for HRC, (2) methodological implications for HRC, and (3) learning from human collaboration.

Design and Simulation of Exoskeleton Robot

Based on the research of lower limb exoskeleton robots and extensive literature review, combined with human anatomy and kinematics, a four-degree-of-freedom lower limb exoskeleton robot was designed, and its three-dimensional model was established using UG software. In the design of the exoskeleton robot, it is required to have a simple structure, zero sensitivity in response speed, and be easy to realize automatic control. The exoskeleton robot designed in this paper uses electric push rods as the driving elements, and the dimensions of each part of the robot are obtained from the national standard human body size table; based on the analysis of the human gait cycle, and using cubic polynomial interpolation to plan the spatial posture of each joint; Adams was used to simulate the movement of the exoskeleton robot, and the motion curves of each joint were obtained.