Freedom Robotic Arm Research Articles

Comparative Analysis of Topology Optimization Platforms for Additive Manufacturing of Robot Arms

Recently, CAD environments have integrated topology optimization (TO) tools, enabling rapid development and manufacturing of parts with optimized mechanical properties. However, different CAD platforms incorporate TO differently, making a comparative analysis necessary. This study aims to systematically compare the efficiency, material usage, and design quality of five commonly used CAD/TO platforms when applied to the topology optimization of a six degrees of freedom robotic arm. The objective is to identify the key differences in how these platforms influence the final design and manufacturing outcomes. Practical validation of results is provided by printing and assembling optimized components into a fully functional robotic arm. Our findings indicate differences in optimization efficiency, material usage, and print time between analyzed platforms. Strengths and weaknesses of each platform are indicated and recommendations for optimization parameters are provided.

Collaborative robot acting as scrub nurse for cataract surgery (CRASCS).

Worldwide, healthcare systems are struggling to tackle a nursing shortage. As per the data released by the American Hospital Association, the healthcare workforce could face a loss of around 5 lakh nurses by the end of the year. Consequently, it could result in those deficiencies, which will be 1.1 million instead of 0.6 million. The current nursing scenario in India as per the Indian Nursing Council (INC), which is a board under the ministry and is responsible for legally confirming and maintaining universal standardized training for nursing, is that the 1.96 nurses out of every 1000 Indians that are there are much behind the World Health Organization's (WHO) recommended figure of 3 nurses per 1000. To mitigate the nurse shortage, a collaborative robotic system was designed that can assist with surgical procedures with a collaborative robot acting as a scrub nurse for cataract surgery (CRASCS) represented in Fig. 1. Accordingly, the model has been built to empower a customized 3d printed 5-Degree of freedom robotic arm by tracking the phase of surgery in real-time and automatically supplying the clinician with the ideal equipment that is needed for the particular phase of surgery. The system is supported with one more model which can identify where the surgical equipment is located within the arm range. The system is also supported with voice commands which help in picking up the right surgical equipment in the middle of any phase of the surgery. In this way, the system could be able to potentially handle the shortage of surgical nurses around the world and benefit humanity.

Inverse kinematic solution and singularity avoidance using a deep deterministic policy gradient approach

<p>The robotic arm emerges as a subject of paramount significance within the industrial landscape, particularly in addressing the complexities of its kinematics. A significant research challenge lies in resolving the inverse kinematics of multiple degree of freedom (M-DOF) robotic arms. The inverse kinematics of M-DOF robotic arms pose a challenging problem to resolve, thus it involves consideration of singularities which affect the arm robot movement. This study aims a novel approach utilizing deep reinforcement learning (DRL) to tackle the inverse kinematic problem of the 6-DOF PUMA manipulator as a representative case within the M-DOF manipulator. The research employs Jacobian matrix for the kinematics system that can solve the singularity, and deep deterministic policy gradient (DDPG) as the kinematics solver. This chosen technique offers enhancing speed and ensuring stability. The results of inverse kinematic solution using DDPG were experimentally validated on a 6-DOF PUMA arm robot. The DDPG successfully solves inverse kinematic solution and avoids the singularity with 1,000 episodes and yielding a commendable total reward of 1,018.</p>

Design and Implementation of a 3 Degrees of Freedom Robotic Arm Powered by Pneumatic Artificial Muscle

The development of a 3-DOF robotic arm powered by pneumatic artificial muscles is represented as an innovative approach in the field of robotics, with the advantages of lightweight and flexible design being combined with the power and control benefits of pneumatic actuation. The design process, challenges, and solutions that were encountered in the development of the robotic arm are outlined in this paper, with an emphasis on its potential applications in industrial and research settings being highlighted. Additionally, the robotic arm’s modular design is enabled to allow easy customization and scalability, making it possible for the arm to be tailored to a wide range of tasks, from precise laboratory work to more robust industrial applications.

Poster 262: Biomechanical Evaluation of New Fixation Techniques for Posterolateral Corner Reconstruction

Objectives: Posterolateral corner (PLC) injuries intricately damage vital knee stabilizers. Both fibular and tibial-based reconstruction techniques are used and are classically described with use of interference screw fixation of the graft at the femur. However, adjustable loop buttons may conserve more bone stock, reduce the risk of tunnel convergence in the setting of multiligament reconstruction, and provide more versatile and reproducible tensioning ability compared to interference screws. Further, tape-reinforced graft suturing has been shown to have favorable biomechanical properties over traditional graft suturing techniques. There is no study comparing interference screw fixation to adjustable loop buttons in the context of tape-reinforced grafts in PLC reconstruction. Therefore, the purpose of this study is to biomechanically compare adjustable loop button fixation with interference screws for fibular collateral ligament and popliteal tendon fixation to the femur for PLC reconstruction. We hypothesize there will be no difference in varus or external rotation laxity between the two methods of fixation. Methods: The biomechanical study was conducted on 10 cadaveric knee specimens in a non-destructive repeated measures sequence using a 6-degree of freedom robotic arm (Fig. 1), under four conditions: (1) Native (2) PLC reconstruction with adjustable-loop suspensory button fixation, (3) PLC reconstruction interference screw fixation, and (4) PLC injured state. Reconstruction was performed using a fibular based technique as described by Arciero et al. FCL and popliteal tendon limbs were tensioned independently with 100N of force. The FCL was tensioned with the knee at 30° of flexion and 3 N∙m of valgus torque in neutral rotation. The popliteal tendon limb was tensioned at 60° of knee flexion with neutral rotation. Biomechanical evaluation consisted of a 5-N∙m external rotation test and a 10-N∙m varus test, performed at 0°, 30°, 60° and 90° of flexion. Results: All differences are presented in the order of 0°, 30°, 60° and 90° of flexion. Cutting the PLC significantly increased external rotation laxity (Fig. 2) (+3.8°, +9.7°, +9.9°, +7.6, all P<0.001) and varus laxity (Fig. 3) (+1.7°, +4.5°, +3.7°, all p<0.001, no significant difference at 90° of flexion) with respect to native. PLC reconstruction with suspensory fixation significantly over constrained external rotation (Fig. 2) (-3.5° P=0.002, -4.3° P<0.001, -4.1° P=0.002, -3.1° P=0.039) and varus (Fig. 3) (-1.5°, -2.1°, -2.4°, -2.1°, all P<0.001). PLC Reconstruction with interference screws similarly over constrained external rotation (Fig. 2) (-4.3°, -5.5°, -5.4°, -4.5°, all P<0.001) and varus (Fig. 3) (-1.8°, -2.5°, -2.9°, -2.8°, all P<0.001). There was no significant difference found between the suspensory fixation and the interference screw fixation in any test. Conclusions: Both reconstruction techniques restored the stability in external rotation and varus stress. No significant differences were found between the two fixation methods, validating both adjustable-loop suspensory buttons and interference screws as viable options for femoral fixation in the setting of PLC reconstruction. However, both methods over-constrained the knee in ER and Varus. This may be due to the increased stiffness of the tape-reinforced graft suturing, or over-tensioning of the grafts during fixation. The study tests a physiologic load but is limited since the specimen is not cyclically loaded or loaded to failure. This study evaluates and compares two PLC reconstruction techniques and their impact on knee stability. These findings provide quantifiable data to aid surgeons in making evidence-based, patient-specific decisions regarding appropriate PLCR technique. Biomechanically, the adjustable-loop suspensory fixation and the interference screw behave very similarly at time zero. Given this, surgeons may select an implant based on their comfort, training and/or patient specific needs. Further research is necessary to determine which implant performs the best in a clinical setting.

Motion Control of 5-Degree of Freedom Humanoid Robot Arm System Using Fuzzy Logic Algorithm

Humanoid robots are the evidence of the rapid advancement of technology in robotics. One of their applications is replacing humans in certain tasks, such as moving goods. For this type of activity, humanoid robots need arms; however, their arm system is not effective enough because of the material used. Thus, this study proposes the use of filament as the material of frames in robot arms. A 5-degree of freedom (DoF) robot arm system was implemented, and the motor worked as the driving force. The movement of this robotic arm was based on proximity and camera sensor readings. Then, the movement control used fuzzy logic with the Sugeno method. During experimental testing, the humanoid robot arm could grip and move objects from one place to another at varying times according to the object type. The length of time obtained depends on the reading of the proximity sensor on the gripper. In another experiment, the humanoid robot arm could shake hands with humans in real time within 36 sec. In conclusion, the results verified the effectiveness of the proposed fuzzy logic controller with the Sugeno method.

Intelligent In situ Printing of Multimaterial Bioinks for First‐Aid Wound Care Guided by Eye‐In‐Hand Robot Technology

AbstractINSIGHT (INtelligent in situ printing Guided by Eye‐in‐Hand robot Technology), an innovative computer vision‐enabled system that combines a depth camera with a 6‐degree of freedom robot arm, empowering it to identify arbitrary areas at various angles through real time adjustments and to enable volumetric printing performed by dynamic image recognition based on color and contour differences is presented. Continuous targeting of multiple wounds at different locations is achieved. The optimized pneumatic valve synchronized with the INSIGHT can print multiple inks with diverse rheological properties to fabricate scaffolds and bandages with the capacity to treat various types of wounds. The design of dual printed modes, such as extrusion and spray, can significantly decrease printing time for large‐scale wounds on an ex vivo porcine model. INSIGHT demonstrates its ability to treat diabetic wounds, using a microgel‐based ink possessing an inherent porous microstructure to facilitate cell infiltration. In vivo verification highlights its adaptability to enable customized care for rapid emergency treatment of trauma patients.

RRR Robotik Kol için Çok Katmanlı Algılayıcı ve Ters Kinematik Karşılaştırması

In this study, the position control simulation of a 3 Degree of Freedom (3DOF) robot arm was compared with machine learning and inverse kinematic analysis separately. The considered robot arm is designed in RRR pattern. In the inverse kinematic analysis of the robot arm, the geometric approach and the analytical approach are used together. Multi-Layer Perceptron (MLP) was used as a machine learning method. Some of the coordinate data that the robot arm can reach in the working space are selected and the MLP model is trained with these data. When training was done with MLP machine learning method, the correlation coefficient (R2) was obtained as 1. Coordinates of 3 different geometric models (helix, star and daisy) that can be included in the working space are used as test data of the MLP model. These tests are simulated in 3D in MATLAB environment. The simulation results were compared with the inverse kinematics analysis data. As a result, Mean Relative Error (MRE) values for helix, star and daisy shapes were calculated as 0.0007, 0.0033 and 0.0011, respectively, in the tests performed. Mean Squared Error (MSE) values were obtained as 0.0034, 0.0065 and 0.0040, respectively. This confirms that the proposed MLP model can operate this system at the desired stability.

Distributed Discrete-time Exponential Sliding Mode Consensus Protocol for Discrete Multi-Agent System Comprise of Multiple Robotic Arms

In this paper, a Distributed Discrete-time Exponential Sliding Mode Consensus (DDESMC) protocol is proposed for the leader-follower consensus of a Discrete Multi-Agent System (DMAS). The proposed protocol ensures not only the minimal consensus effort and reaching time for the consensus among the agents but also the minimum consensus deviation in the order of O(T3). The consensus stability of DMAS with the proposed protocol is analyzed using Lyapunov theory and the maximum number of reaching steps required for achieving the consensus among all agents is calculated. The proposed protocol is validated in a simulation and experimental setup comprised of multiple 2-Degree of Freedom (DOF) robotic arms where one of the robotic arms is real, and others are virtual. Further, the consensus performance compared with the existing protocol in the literature, and it is inferred that the proposed protocol outperforms it in terms of time and effort required to achieve the consensus and the deviation from the consensus.

Experimental and simulation study of a four-degree of freedom robot arm moving through space planner path

Experimental and simulation study of a four-degree of freedom robot arm moving through space planner path

Assessing layer deviations and correction for robotic polymer 3D printing applications

Additive manufacturing (AM), often referred to as 3D printing, is a manufacturing technique that involves the creation of complex objects layer-by-layer while providing design flexibility. The broad spectrum of additive manufacturing applications in aerospace, medicine, automotive industries, etc., using high-value materials necessitates a precise final product with minimal wastage. However, the print's dependence on optimizing parameters such as nozzle diameter, printing speed, extrusion speed, nozzle temperature and other multifaceted factors can contribute to deviations from the intended design. This paper introduces a closed-loop in-situ assessment of layer height deviations using point cloud data to ensure real-time printed part modification. The printing is done using a direct-fed pellet screw extruder mounted on top of 6 degrees of freedom robotic arm. A structured light 3D scanner is used to obtain point cloud data. A Robot Operating System (ROS) based digital toolchain is employed to have seamless communication between all nodes of the AM system. The layer-by-layer printing is observed using an in-house CAM solution, which examines the point cloud data and compares it to the original CAD model. The deviations are analyzed, and the path of the next layer is re-planned to adjust for the digression in the previous layer. This control loop ensures that the final product meets the desired quality standards at minimum cost and efficient time and increases the opportunity for rapid prototyping and iterative design improvements.

An Intelligent Obstacle Avoidance Method for Six Degree of Freedom Robotic Arm Based on Assembly Sequence Planning

Abstract Autonomous operation planning of robotic arms under complex task constraints is still a difficult problem in the current research in this direction, and the existing operation planning methods are facing challenges and urgently need to break through the technical bottleneck. This paper proposes an improved RRT algorithm for six-degree-of-freedom robotic arms, which can be used for obstacle avoidance path planning. Based on the assembly sequence planning method, combining the advantages of RRT and RRT-connect algorithm, applying the idea of target sampling to strengthen the convergence of the algorithm to the target point search, introducing the greedy algorithm to improve the efficiency of the algorithm, combining with the five times of the B-spline interpolation on the path of the smoothing optimization, to shorten the planning path time and length. The Robotics Toolbox toolkit in MATLAB is used to count the time, number of samples, and path length required for the planning of RRT and the improved RRT algorithm, and the dynamic planning library is used to configure the algorithm and verify the path planning effect of the improved algorithm. Compared with the traditional RRT algorithm, using the proposed SDPS-RRT Connect algorithm for six-degree-of-freedom robotic arm path planning, the minimum distance of the connecting rod from the obstacle is 51.4948cm, which is greater than the standard safety distance of 45cm, which verifies the feasibility of the algorithm in practical applications.

Simulation of Kinematic and Dynamic Model of Two Degrees of Freedom Robot Arm Using Simulink

The aim of this study is to realize the physical model of a robot arm with two degrees of freedom in the MATLAB Simulink environment, to show that the physical model of the robot arm matches the mathematical model and that the results of these models match. For this purpose, kinematic and dynamic modeling of a two-degree-of-freedom robotic arm is performed in the MATLAB Simulink environment. To ensure the accuracy of the physical model created in the MATLAB Simulink environment, mathematical equations are defined to a function within the physical model, in other words, a mathematical model is created. The kinematic equations of the robotic arm are examined in two steps as forward kinematics and inverse kinematics equations, and the geometric approach is used when obtaining the kinematic equations. The Lagrange-Euler method is used to obtain dynamic equations. The results obtained show that the mathematical kinematic and dynamic equations match the physical model in the MATLAB Simulink environment and reveal that the system is reliable.

Design and development of latex cup collector robot

Global rubber production has declined over the past few years as a result of a number of variables, including both environmental and human factors. In this paper, an automated robot prototype that collects latex cups was developed to improve global rubber production by assisting workers in rubber plantations. The robot was built on a mobile platform with a motorized Five Degrees of Freedom (DoF) robotic arm, Ackermann steering, double wishbone suspension, rear-wheel drive and a latex storage tank to store the latex collected from the trees. The robot was equipped with ultrasonic sensors and a camera module to locate latex cups and rubber trees so that it could move and perform tasks accurately. In addition, encoder sensor modules were used to improve the accuracy of the movements by measuring the rotational speed of the motors. The yield strength of the PLA plastic material used in developing the latex cup collector robot is 7.00 x 107N/m2 and the maximum stress of the critical parts should not exceed the maximum yield strength of the PLA plastic. In mobility test, the robot is able to travel through obstacles of 10mm and 15mm height. The topple angle of the robot in the balancing test is greater than 37°, ensuring the stability of the robot.

Robotic arm trajectory tracking method based on improved proximal policy optimization

To study the method of trajectory tracking for robotic arms, the traditional tracking method has low accuracy and cannot realize the complex tracking tasks. Compared with traditional methods, deep reinforcement learning is an effective scheme with the advantages of robustness and solving complex problems. This study aims to improve the tracking efficiency of robotic arms based on deep reinforcement learning. Thereby, we propose an approach to improve the proximal policy optimization (Improved-PPO) in this paper, which can be applied to multiple degrees of freedom robotic arms for trajectory tracking. In this study, proximal policy optimization (PPO) and model predictive control (MPC) are integrated to provide an effective algorithm for robotic arm applications. MPC is employed for trajectory prediction to design the controller. Further, the Improved-PPO algorithm is employed for trajectory tracking. The Improved-PPO algorithm is further compared with the asynchronous advantage actor-critic (A3C) and PPO algorithms. The simulation results show that the convergence speed of the Improved-PPO algorithm is increased by 84.3% and 15.4% compared with the A3C and PPO algorithms. This method provides a new research concept for robotic arm trajectory tracking.

CBMC: A Biomimetic Approach for Control of a 7-Degree of Freedom Robotic Arm.

Many approaches inspired by brain science have been proposed for robotic control, specifically targeting situations where knowledge of the dynamic model is unavailable. This is crucial because dynamic model inaccuracies and variations can occur during the robot's operation. In this paper, inspired by the central nervous system (CNS), we present a CNS-based Biomimetic Motor Control (CBMC) approach consisting of four modules. The first module consists of a cerebellum-like spiking neural network that employs spiking timing-dependent plasticity to learn the dynamics mechanisms and adjust the synapses connecting the spiking neurons. The second module constructed using an artificial neural network, mimicking the regulation ability of the cerebral cortex to the cerebellum in the CNS, learns by reinforcement learning to supervise the cerebellum module with instructive input. The third and last modules are the cerebral sensory module and the spinal cord module, which deal with sensory input and provide modulation to torque commands, respectively. To validate our method, CBMC was applied to the trajectory tracking control of a 7-DoF robotic arm in simulation. Finally, experiments are conducted on the robotic arm using various payloads, and the results of these experiments clearly demonstrate the effectiveness of the proposed methodology.

The effect of ionizing radiation on robotic trajectory movement and electronic components

Robotics applications are greatly needed in hazardous locations, e.g., fusion and fission reactors, where robots must perform delicate and complex tasks under ionizing radiation conditions. The drawback is that some robotic parts, such as active electronics, are susceptible to radiation. It can lead to unexpected failures and early termination of the robotic operation. This paper analyses the ionizing radiation effect from 0.09 to 1.5 Gy/s in robotic components (microcontrollers, servo motors and temperature sensors). The first experiment compares the performance of various microcontroller types and their actuators and sensors, where different mitigation strategies are applied, such as using Radiation-Hardened (Rad-Hard) microcontrollers or shielding. The second and third experiments analyze the performance of a 3-Degrees of Freedom (DoF) robotic arm, evaluating its componentsʼ responses and trajectory. This study enhances our understanding and expands our knowledge regarding radiationʼs impact on robotic arms and components, which is useful for defining the best strategies for extending the robotsʼ operational lifespan, especially when performing maintenance or inspection tasks in radiation environments.

Dynamic Optimization Fabrics for Motion Generation

Optimization fabrics are a geometric approach to real-time local motion generation, where motions are designed by the composition of several differential equations that exhibit a desired motion behavior. We generalize this framework to dynamic scenarios and nonholonomic robots and prove that fundamental properties can be conserved. We show that convergence to desired trajectories and avoidance of moving obstacles can be guaranteed using simple construction rules of the components. In addition, we present the first quantitative comparisons between optimization fabrics and model predictive control and show that optimization fabrics can generate similar trajectories with better scalability, and thus, much higher replanning frequency (up to 500 Hz with a 7 degrees of freedom robotic arm). Finally, we present empirical results on several robots, including a nonholonomic mobile manipulator with 10 degrees of freedom and avoidance of a moving human, supporting the theoretical findings.

The Biomechanical Role of the Deltoid Ligament on Ankle Stability: Injury, Repair, and Augmentation

Background: Deltoid ligament injuries occur in isolation as well as with ankle fractures and other ligament injuries. Both operative treatment and nonoperative treatment are used, but debate on optimal treatment continues. Likewise, the best method of surgical repair of the deltoid ligament remains unclear. Purpose: To determine the biomechanical role of native anterior and posterior components of the deltoid ligament in ankle stability and to determine the efficacy of simple suture versus augmented repair. Study Design: Controlled laboratory study. Methods: Ten cadaveric ankles (mean age, 51 years; age range, 34-64 years; all male specimens) were mounted on a 6 degrees of freedom robotic arm. Each specimen underwent biomechanical testing in 8 states: (1) intact, (2) anterior deltoid cut, (3) anterior repair, (4) tibiocalcaneal augmentation, (5) deep anterior tibiotalar augmentation, (6) posterior deltoid cut, (7) posterior repair, and (8) complete deltoid cut. Testing consisted of anterior drawer, eversion, and external rotation (ER), each performed at neutral and 25° of plantarflexion. A 1-factor, random-intercepts, linear mixed-effect model was created, and all pairwise comparisons were made between testing states. Results: Cutting the anterior deltoid introduced ER (+2.1°; P = .009) and eversion laxity (+6.2° of eversion; P < .001) at 25 degrees of plantarflexion. Anterior deltoid repair restored native ER but not eversion. Tibiocalcaneal augmentation reduced eversion laxity, but tibiotalar augmentation provided no additional benefit. The posterior deltoid tear showed no increase in laxity. Complete tear introduced significant anterior translation, ER, and eversion laxity (+7.6 mm of anterior translation, +13.8° ER and +33.6° of eversion; P < .001). Conclusion: A complete deltoid tear caused severe instability of the ankle joint. Augmented anterior repair was sufficient to stabilize the complete tear, and no additional benefit was provided by posterior repair. For isolated anterior tear, repair with tibiocalcaneal augmentation was the optimal treatment. Clinical Relevance: Deltoid repair with augmentation may reduce or avoid the need for prolonged postoperative immobilization and encourage accelerated rehabilitation, preventing stiffness and promoting earlier return to preinjury activity.

Design and Analysis of a Four DoF Robotic Arm with Two Grippers Used in Agricultural Operations

Both academic and commercial interest in agricultural robots has increased recently. This is due to the fact that agricultural robots address significant issues such as seasonal labor shortages during harvest and the rising concern over environmentally friendly practices. Because of these, several distinct agricultural robots have already been created for a variety of purposes, with varying degrees of success, including monitoring, spraying, harvesting, transport, etc. As a result, agriculture automation became unfeasible and unprofitable. The purpose of this study is to provide a new methodology for multitasking in performing agriculture operations by designing a 4 Degrees of freedom (4DoF) robotic arm with a new mechanism that has a different configuration with 2 grippers. We did kinematics and kinetics calculations using Denavit-Hardenberg (D-H) method with Lagrangian mechanics, and with the help of Christoffel Symbols of the First Kind, also We used Robot Operating System (ROS) to provide potential solutions using it. It is easy to be paired with other open-source technologies, such as android or IoT technologies. The robot arm can work synchronously with other hardware, sensors, cameras, and agricultural machines concerning farming operations. In conclusion, we believe that this new configuration will open a door for agricultural tasks to be easily automated and achieved using robotic technologies.