Performance Of Robot Research Articles

Design and Development of a Package Delivery Robot

This research focuses on the design and development of a package delivery robot, comprising an electronic housing and a storage unit. The robot is remotely controlled through a website, equipped with obstacle detection capabilities, and capable of unlocking the storage unit. However, movement is limited when the storage unit is installed on the electronic housing. The objective of this project was to build a package delivery robot that could operate in organised environments, such as universities and estates. The project commenced with extensive research on existing delivery robots, analysing their strengths and weaknesses. Based on this analysis, a set of design requirements was formulated, emphasising compact size, lightweight construction, and user-friendly operation. A custom control system was developed, enabling robot navigation, while sensors were integrated to facilitate obstacle avoidance and pedestrian safety. The first chassis of the robot was constructed using lightweight sheet metal, but turned out to be too heavy for the motors to drive, so the chassis was reconstructed using corrugated cardboard. To evaluate its performance, the robot underwent rigorous testing in a simulated urban environment. The robot has a speed of 0.5 m/s, and receives commands at a speed of 0.0068 nano seconds. It also consumes a power of 120 watts. While the robot demonstrated below-average performance in these aspects, limitations were identified, such as the inability to make left or right turns due to the shaft that connects the tyre and the motor being short. In conclusion, this research introduces a package delivery robot that has the potential to significantly enhance the customer delivery experience in urban environments. The robot represents progress in delivery system development and provides valuable insights into the challenges and opportunities within the field of mechatronics. The introduction, methodology, results, and conclusion framework used in this project offers a comprehensive understanding of the research and development process, the robot's performance, and its impact on the field.

Simulation of artificial intelligence robots in dance action recognition and interaction process based on machine vision

Artificial intelligence robots based on machine vision have shown great potential in dance action recognition and interaction. In order to perform action recognition, a large amount of dance action video data was collected as the basis for training and testing the model. In motion recognition, various computer vision techniques are used to extract motion features from images or videos to capture key information of dance movements. Machine learning technology was adopted to construct an action classification model. By using the data collected in the early stage and the extracted features, an efficient and accurate classifier has been studied and trained. It can classify the input dance actions into different categories, segment continuous video frames into different action segments, and ensure accurate differentiation of different dance actions during the recognition process, avoiding misjudgment or confusion. By accurately capturing and analyzing the posture information of the human body, we can better understand and simulate dance movements, and enhance the performance and realism of artificial intelligence robots in dance interactions. The experimental results show that the system can accurately recognize various dance movements and achieve good interaction with users.

Agents of Autonomy: A Systematic Study of Robotics on Modern Hardware

As robots increasingly permeate modern society, it is crucial for the system and hardware research community to bridge its long-standing gap with robotics. This divide has persisted due to the lack of (i) a systematic performance evaluation of robotics on different computing platforms and (ii) a comprehensive, open-source, cross-platform benchmark suite. To address these gaps, we present a systematic performance study of robotics on modern hardware and introduce RoWild, an open-source benchmark suite for robotics that is comprehensive and cross-platform. Our workloads encompass a broad range of robots, including driverless vehicles, pilotless drones, and stationary robotic arms, and we evaluate their performance on a spectrum of modern computing platforms, from low-end embedded CPUs to high-end server-grade GPUs. Our findings reveal that current architectures experience significant inefficiencies when executing robotic workloads, highlighting the need for architectural advancements. We discuss approaches for meeting these requirements, offering insights for improving the performance of robotics. The full version of the paper is available in [11], and the source code of the benchmark suite is available in [2].

Enhancing Surgical Robotics: A Dynamic Model and Optimized Control Strategy for Cable-Driven Continuum Robots

Abstract This paper tackles the challenges encountered in surgical continuum robotics by introducing a dynamic model tailored for a cable-driven continuum robot. The intricacies of dynamic modeling and control frequently lead to suboptimal outcomes. Prior studies have often lacked comprehensive descriptions of individual robot component movements, thereby impeding control processes, especially in the presence of external disturbances. Although machine learning-based models show promise across different domains, they face hurdles in continuum robotics due to the complexity of the systems involved. Traditional mathematical models, in contrast, offer explicit equations, providing better interpretability, unlike machine learning models that may struggle with generalization, especially in highly nonlinear systems like continuum robots. The developed model adeptly captures the kinematic and dynamic constraints of various robot segments, serving as the foundation for a robust optimized control strategy. This strategy, which integrates computed torque control and particle swarm optimization (PSO-CTC), enables real-time computation of joint torques based on feedback, ensuring precise and stable task execution even amidst external perturbations. Comparative analysis with an optimized proportional integral derivative (OPID) controller unequivocally demonstrates the superiority of the optimized computed torque controller (OCTC) in settling time, overshoot, and robustness against disturbances. This advancement represents a noteworthy contribution to robotics, with the potential to significantly enhance continuum robot performance in surgical and inspection applications, thereby fostering innovative advancements across various fields.

Research and Implementation of Pneumatic Amphibious Soft Bionic Robot

To meet the requirements of amphibious exploration, ocean exploration, and military reconnaissance tasks, a pneumatic amphibious soft bionic robot was developed by taking advantage of the structural characteristics, motion forms, and propulsion mechanisms of the sea lion fore-flippers, inchworms, Carangidae tails, and dolphin tails. Using silicone rubber as the main material of the robot, combined with the driving mechanism of the pneumatic soft bionic actuator, and based on the theory of mechanism design, a systematic structural design of the pneumatic amphibious soft bionic robot was carried out from the aspects of flippers, tail, head–neck, and trunk. Then, a numerical simulation algorithm was used to analyze the main executing mechanisms and their coordinated motion performance of the soft bionic robot and to verify the rationality and feasibility of the robot structure design and motion forms. With the use of rapid prototyping technology to complete the construction of the robot prototype body, based on the motion amplitude, frequency, and phase of the bionic prototype, the main execution mechanisms of the robot were controlled through a pneumatic system to carry out experimental testing. The results show that the performance of the robot is consistent with the original design and numerical simulation predictions, and it can achieve certain maneuverability, flexibility, and environmental adaptability. The significance of this work is the development of a pneumatic soft bionic robot suitable for amphibious environments, which provides a new idea for the bionic design and application of pneumatic soft robots.

Simulation of entertainment interactive robots based on intelligent algorithms in personalized fitness training systems

In the current context of rapid development of information technology and AI, entertainment interactive robots can play an auxiliary role in fitness training. Intelligent technical services can provide athletes with timely training course information and gamified sports training. Various data will also be uploaded to technical platforms for analysis. This article studies the design of a personalized fitness training system for entertainment interactive robots based on intelligent algorithms. Firstly, this article analyzes the main technologies of photon integrated biosensors, establishes a linear photon integrated biosensor imaging model. Choose to use intelligent algorithms to optimize coverage for wireless sensor networks. This problem is transformed into a mathematical function model, and then the optimal solution is sought through algorithms, effectively reducing the energy consumption of the network and extending its lifespan. The system improves interaction with humans by collecting training action videos, automatically recognizes the types of human training actions, and automatically extracts key postures from training actions for comparison and analysis with standard postures. The practice and research of human–computer interaction have shown that in addition to the actual performance of social robots, the emotional interaction of social robots can also affect people's trust in their abilities.

Kinematic Modeling and Performance Analysis of a 5-DoF Robot for Welding Applications

Robotic manipulators are critical for industrial automation, boosting productivity, quality, and safety in various production applications. Key factors like the payload, speed, accuracy, and reach define robot performance. Optimizing these factors is crucial for future robot applications across diverse fields. While 6-Degrees-of-Freedom (DoF)-articulated robots are popular due to their diverse applications, this research proposes a novel 5-DoF robot design for industrial automation, featuring a combination of three prismatic and two revolute (2R) joints, and analyzes its workspace. The proposed techno-economically efficient design offers control over the robot manipulator to achieve any reachable position and orientation within its workspace, replacing traditional 6-DoF robots. The kinematic model integrates both parallel and serial manipulator principles, combining a Cartesian mechanism with rotational mechanisms. Simulations demonstrate the end effector’s flexibility for tasks like welding, additive manufacturing, and material inspections, achieving the desired position and orientation. The research encompasses the design of linear and rotational actuators, kinematic modeling, Human–Machine Interface (HMI) development, and welding application integration. The developed robot demonstrates a superior performance and user-friendliness in welding. The experimental work validates the design’s optimized joint trajectories, efficient power usage, singularity avoidance, easy access in application areas, and reduced costs due to fewer actuators.

How to integrate robotic training in surgical residency? An example of a 2-week robotic rotation.

General surgery residents should be proficiently trained in robotic surgery. However, there is currently no standardized robotic training curriculum. We aimed to evaluate two approaches to a robotic curriculum and how implementing a virtual reality (VR) simulation curriculum improves trainee robotic performance. From 2019 to 2022, two models of a robotic training curriculum were examined: an in-unit rotation (IUR) and a 2-week curriculum (2WR). The VR curriculum was completed using the da Vinci® Skill Simulator. The curriculum used a pre/post-test design. Residents completed a pre-test that consisted of 4 VR exercises (graded 0-100%) and 3 inanimate box trainer exercises (graded using modified Objective Structured Assessment of Technical Skills). Then, residents completed a VR curriculum of 23 modules. Following the curriculum, residents were given a post-test with the same pre-test exercises. Time necessary to complete the curriculum and compliance were recorded. Of the 11 residents who participated in the IUR, 4 completed the VR curriculum. Comparatively, 100% (n = 23) of residents in the 2WR completed the curriculum. Average time to complete the VR curriculum was 3.8h. After completion of the 2WR curriculum, resident performance improved from pre-test to post-test: VR test scores increased (160% vs 223%, p < 0.001), OSATS scores increased (15.0 vs 21.0, p < 0.001), and time to complete inanimate exercises decreased (1083 vs 756s, p = 0.001). Residents who mastered all modules had higher post-test VR scores (241% vs 214%, p = 0.024). General surgery residents demonstrated improved compliance with the 2WR. The VR curriculum improved resident robotic performance in both virtual and inanimate domains.

Trajectory Planning Research Based on Rapidly-exploring Random Trees (RRT) Algorithm and Modified Forms

With the rapid advancement of computer technology, robots have become indispensable in various fields. Trajectory planning plays a crucial role in optimizing robot performance by enhancing work efficiency and reducing operational costs. While the widely used Rapidly-exploring Random Trees (RRT) algorithm is effective in path planning, it often generates non-optimal paths with poor smoothness. By incorporating elements from RRT-Connect and reverse optimization, the algorithm can efficiently navigate through intricate and dynamic surroundings. Furthermore, the utilization of cubic polynomial interpolation in optimizing path curves adds a layer of sophistication to the trajectory planning process. This interpolation technique allows for the creation of smoother and more natural path trajectories, reducing jerky movements and enhancing overall motion control precision. The paths produced by the enhanced RRT algorithm demonstrate increased continuity and visual attractiveness, crucial for tasks necessitating accurate and elegant robotic motions. The improved algorithm showcases reduced path length and time consumption, as well as enhanced path smoothness. Particularly, relative to the traditional RRT approach, the time consumption has dropped by 69.15% and the median duration of the paths has fallen by 21.11%. These improvements signify a substantial advancement in trajectory planning for robots, offering more efficient and smoother paths for robotic operations across various applications.

Evaluation of Biomechanical and Mental Workload During Human-Robot Collaborative Pollination Task.

The purpose of this study is to identify the potential biomechanical and cognitive workload effects induced by human robot collaborative pollination task, how additional cues and reliability of the robot influence these effects and whether interacting with the robot influences the participant's anxiety and attitude towards robots. Human-Robot Collaboration (HRC) could be used to alleviate pollinator shortages and robot performance issues. However, the effects of HRC for this setting have not been investigated. Sixteen participants were recruited. Four HRC modes, no cue, with cue, unreliable, and manual control were included. Three categories of dependent variables were measured: (1) spine kinematics (L5/S1, L1/T12, and T1/C7), (2) pupillary activation data, and (3) subjective measures such as perceived workload, robot-related anxiety, and negative attitudes towards robotics. HRC reduced anxiety towards the cobot, decreased joint angles and angular velocity for the L5/S1 and L1/T12 joints, and reduced pupil dilation, with the "with cue" mode producing the lowest values. However, unreliability was detrimental to these gains. In addition, HRC resulted in a higher flexion angle for the neck (i.e., T1/C7). HRC reduced the physical and mental workload during the simulated pollination task. Benefits of the additional cue were minimal compared to no cues. The increased joint angle in the neck and unreliability affecting lower and mid back joint angles and workload requires further investigation. These findings could be used to inform design decisions for HRC frameworks for agricultural applications that are cognizant of the different effects induced by HRC.

COMPARISON OF MECHANICAL DESIGN AND FLOW ANALYSIS OF QUADRUPED ROBOTS

In recent years, there has been a trend of developing innovative technologies inspired by living creatures in nature. Quadruped robots, in particular, have emerged as walking mobile systems with articulated leg structures that can skilfully perform dynamic movements that wheeled systems are limited to. These robots offer advantages in technical criteria such as manoeuvrability, cross-capability, controllability, terrain adaptability and stability. It is important to note that this evaluation is based on objective technical criteria rather than subjective opinions. This study compares the advantages and disadvantages of quadruped robots to wheeled systems. It highlights that quadruped robots outperform wheeled systems in manoeuvrability, obstacle overcoming, and speed, particularly in rough terrains. The study also suggests that designers of quadruped robots should consider aerodynamic factors, which are often overlooked. Flow analysis using the finite element method is crucial in robot design to enhance aerodynamic performance. This paper aims to comprehensively analyse the flow structure around quadruped robots using Computational Fluid Dynamics and investigate passive flow control methods to reduce the drag coefficient (Cd). The study examines four different robots, and the resulting Cd average percentage calculations are presented. The aerodynamic efficiency of Robot 4 compared to Robot 2 was found to be 95%. Similarly, the aerodynamic efficiency of Robot 3 was determined to be 28% compared to Robot 2. Additionally, it was determined that the aerodynamic efficiency of Robot 2 was 76% compared to Robot 1. These results provide an important comparison to understand the energy efficiency, differences in aerodynamic performance and relative effectiveness of quadruped robots.

P.152 In-vivo accuracy of pedicle screws utilizing a supervisory controlled 7DOF robot with OCT guidance

Background: Pedicle screw fixation is an important technique in spine surgery. Violation of the pedicle can lead to neurovascular injury. Due to excellent pose repeatability, robotic technology may improve accuracy. Existing surgical spine robots use surgical assist architecture. This work explores the performance of a supervisory-control architecture robot (8i Robotics) for autonomous pedicle instrumentation. Methods: 3 porcine subjects underwent pedicle instrumentation utilizing the 7dof robot and were observed for 24 hours. Post-operative CT assessed screw location. Screws were graded clinically with the Gertzbein-Robbins Scale (GRS). Precision was assessed by a customized image processing pipeline. Euclidean error was calculated at screw head and screw tip. All points were normalized to a nominal screw, and confidence ellipses generated. Results: All animals were neurologically intact at 24 hours. All screws where GRS A. Mean tip and head Euclidean error where 2.47+/−1.25mm and 2.25+/-1.25mm respectively. Major and minor axes of the confidence ellipse at 99% was 2.19mm, and 1.28mm, and 2.07mm, and 0.42mm for tip and head respectively. Conclusions: 100% of screws obtained satisfactory clinical grading, with intact function in all animals post-operatively. This shows the capability of a supervisory-controlled 7DOF robot with OCT registration. Further investigation is warranted to further explore robotic capabilities, safety, and cost effectiveness.

Dynamic Analysis of the Locomotion Mechanism in Foxtail Robots: Frictional Anisotropy and Bristle Diversity.

This study investigated the locomotion mechanism of foxtail robots, focusing on the frictional anisotropy of tilted bristles under the same friction coefficient and propulsion strategy using bristle diversity. Through dynamic analysis and simulations, we confirmed the frictional anisotropy of tilted bristles and elucidated the role of bristle diversity in generating propulsive force. The interaction between contact nonuniformity and frictional anisotropy was identified as the core principle enabling foxtail locomotion. Simulations of foxtail robots with multiple bristles demonstrated that variations in bristle length, angle, and deformation contribute to propulsive force generation and environmental adaptability. In addition, this study analyzed the influence of major design parameters on frictional anisotropy, highlighting the critical roles of body height, bristle length, stiffness, reference angle, and friction coefficient. The proposed guidelines for designing foxtail robots emphasize securing bristle nonuniformity and inducing contact nonuniformity. The simulation framework presented enables the quantitative prediction and optimization of foxtail robot performance. This research provides valuable insights into foxtail robot locomotion and lays a foundation for the development of efficient and adaptive next-generation robots for diverse environments.

Design and Experiment of an Ankle Rehabilitation Robot After Fracture Surgery

Abstract In order to address the problem of functional rehabilitation after ankle fracture surgery, this paper presented a novel ankle fracture rehabilitation robot. The robot adopted R-3RRS-P hybrid structure, which was simple in structure and had two working modes: rehabilitation training and motion axis switching. Compared with the existing ankle rehabilitation robot, the proposed robot could simulate more realistic kinematics of the ankle joint complex. Additionally, different body types of patients could be adapted. The kinematic and static models were established in detail using geometric method and screw theory. The coverage of the healthy ankle motion ability was formulated as an optimization problem to improve the robot's performance. Multi-objective optimal design was carried out to determine the dimensional parameters. The interference-free working space was calculated by numerical method. A prototype of the proposed robot was developed, and a series of experiments were performed to evaluate the function and feasibility of the proposed robot.

Design and implementation of an autonomous fire-extinguishing robot with SMS alert functionality

Fire outbreak represents a formidable threat, capable of causing loss of life, property destruction, and permanent injuries. Firefighters bravely confront these hazards, placing themselves at serious risk to protect communities. Despite the inherent dangers, their selfless service remains vital. Among recent technological advancements, firefighting robots have emerged as significant tools for mitigating such risks. These robots utilize machine learning and cutting-edge sensor technologies to enhance fire detection accuracy, minimizing false alarms. To improve the performance of the fire robot, this study designed and implemented an Arduino UNO microcontroller based on the ATmega32 and developed using C++ language. In addition to equipping it with SMS capability that allows it to notify the concerned entity about an outbreak, the developed robot operates autonomously thereby minimizing human error in its operation. With the aid of the ultrasonic sensors, the robot navigates and avoids obstacles collision with high precision. Integrated with flame and smoke sensors controlled by the microcontroller ensures swift fire detection. By autonomously sprinkling water from a mounted container, it effectively suppresses fires. Through this innovative design, the study aims to bolster fire response capabilities, reducing reliance on human intervention and enhancing safety for both firefighters and civilians. From the performance evaluation carried out on the developed robot, it was observed that the robot has exhibited an effective performance in detecting and extinguishing fires using the various sensors.

CardioXplorer: An Open-Source Modular Teleoperative Robotic Catheter Ablation System

Atrial fibrillation, the most prevalent cardiac arrhythmia, is treated by catheter ablation to isolate electrical triggers. Clinical trials on robotic catheter systems hold promise for improving the safety and efficacy of the procedure. However, expense and proprietary designs hinder accessibility to such systems. This paper details an open-source, modular, three-degree-of-freedom robotic platform for teleoperating commercial ablation catheters through joystick navigation. We also demonstrate a catheter-agnostic handle interface permitting customization with commercial catheters. Collaborating clinicians performed benchtop targeting trials, comparing manual and robotic catheter navigation performance. The robot reduced task duration by 1.59 s across participants and five trials. Validation through mean motion jerk analysis revealed 35.2% smoother robotic navigation for experts (≥10 years experience) compared to the intermediate group. Yet, both groups achieved smoother robot motion relative to the manual approach, with the experts and intermediates exhibiting 42.2% and 13.6% improvements, respectively. These results highlight the potential of this system for enhancing catheter-based procedures. The source code and designs of CardioXplorer have been made publicly available to lower boundaries and drive innovations that enhance procedure efficacy beyond human capabilities.

Two-step calibration of 6-DOF industrial robots by grouping kinematic parameters based on distance constraints

The positioning accuracy of industrial robots is critical for their applications, which can be improved through calibration. This paper proposes a two-step calibration method for six-degree-of-freedom (6-DOF) industrial robots to reduce couplings of their modified Denavit-Hartenberg (MD-H) model parameters during optimization processes of kinematic calibration. In this method, a distance error model is established based on the distance constraints, and the MD-H model parameters of the industrial robots are identified group by group using the Levenberg-Marquardt (LM) algorithm. To determine the optimal MD-H model parameter grouping, the different grouping strategies are simulated and analyzed. In the proposed method, the coordinate system transformation between the measurement frame and the robot base frame can be avoided based on the distance error model, thereby reducing the errors introduced by the coordinate system transformation during the calibration process. Finally, the proposed two-step calibration method is verified through an experiment. The experimental result shows that the distance/positioning accuracy on the robot end-effector is improved from 0.602 mm/2.7317 mm to 0.151 mm/0.717 mm after calibration. The presented study may be beneficial for improving performance of industrial 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.

Crystallization-Inspired Design and Modeling of Self-Assembly Lattice-Formation Swarm Robotics.

Self-assembly formation is a key research topic for realizing practical applications in swarm robotics. Due to its inherent complexity, designing high-performance self-assembly formation strategies and proposing corresponding macroscopic models remain formidable challenges and present an open research frontier. Taking inspiration from crystallization, this paper introduces a distributed self-assembly formation strategy by defining free, moving, growing, and solid states for robots. Robots in these states can spontaneously organize into user-specified two-dimensional shape formations with lattice structures through local interactions and communications. To address the challenges posed by complex spatial structures in modeling a macroscopic model, this work introduces the structural features estimation method. Subsequently, a corresponding non-spatial macroscopic model is developed to predict and analyze the self-assembly behavior, employing the proposed estimation method and a stock and flow diagram. Real-robot experiments and simulations validate the flexibility, scalability, and high efficiency of the proposed self-assembly formation strategy. Moreover, extensive experimental and simulation results demonstrate the model's accuracy in predicting the self-assembly process under different conditions. Model-based analysis indicates that the proposed self-assembly formation strategy can fully utilize the performance of individual robots and exhibits strong self-stability.

Residents underestimate their robotic performance: evaluating resident robotic console participation time

Lack of formal national robotic curriculum results in a void of knowledge regarding appropriate progression of autonomy in robotic general surgery training. One midwestern academic surgical training program has demonstrated that residents expect to independently operate more on the robotic console than they perceive themselves to do. As such, our study sought to evaluate expectations of residents and faculty regarding resident participation versus actual console participation time (CPT) at a community general surgery training program. We surveyed residents and faculty in two phases. Initially, participants were asked to reflect on their perceptions and expectations from the previous six months. The second phase included surveys (collected over six months) after individual cases with subjective estimation of participation versus CPT calculated by the Intuitive Surgical, Inc. MyIntuitive application. Using Mann–Whitney U-Test, we compared resident perceptions of CPT to actual CPT by case complexity and post-graduate year (PGY). Faculty (n = 7) estimated they allowed residents to complete a median of 26–50% of simple and 0–25% of complex cases in the six months prior to the study. They expected senior residents (PGY-4 and PGY-5) to complete more: 51–75% of simple and 26–50% of complex cases. Residents (n = 13), PGY-2–PGY-5, estimated they completed less than faculty perceived (0–25% of simple and 0–25% of complex cases). Sixty-six post-case (after partial colectomy, abdominoperoneal resection, low anterior resection, cholecystectomy, inguinal/ventral hernia repair, and others) surveys were completed. Residents estimated after any case that they had completed 26–50% of the case. However, once examining their MyIntuitive report, they actually completed 51–75% of the case (median). Residents, especially PGY-4 and 5, completed a higher percentage than estimated of robotic cases. Our study confirms that residents can and should complete more of (and increasingly complex) robotic cases throughout training, like the transition of autonomy in open and laparoscopic surgery.