Design and development of DrawBot using image processing

Extracting text from an image and reproducing them can often be a laborious task. We took it upon ourselves to solve the problem. Our work is aimed at designing a robot which can perceive an image shown to it and reproduce it on any given area as directed. It does so by first taking an input image and performing image processing operations on the image to improve its readability. Then the text in the image is recognized by the program. Points for each letter are taken, then inverse kinematics is done for each point with MATLAB/Simulink and the angles in which the servo motors should be moved are found out and stored in the Arduino. Using these angles, the control algorithm is generated in the Arduino and the letters are drawn.

IMU-derived kinematics detect gait differences with age or knee osteoarthritis but differ from marker-derived inverse kinematics

Common in-lab, marker-based gait analyses may not represent daily, real-world gait. Real-world gait analyses may be feasible using inertial measurement units (IMUs), especially with recent advancements in open-source methods (e.g., OpenSense). Before using OpenSense to study real-world gait, we must determine whether these methods: (1) estimate joint kinematics similarly to traditional marker-based motion capture (MoCap) and (2) differentiate groups with clinically different gait mechanics. Healthy young and older adults and older adults with knee osteoarthritis completed this study. We captured MoCap and IMU data during overground walking at self-selected and faster speeds. MoCap and IMU kinematics were computed with appropriate OpenSim workflows. We tested whether sagittal kinematics differed between MoCap- and IMU-derived data, whether tools detected between-group differences similarly, and whether kinematics differed between tools by speed. MoCap data showed more flexion than IMU data (hip: 0-47 and 65-100% stride, knee: 0-38 and 58-91% stride, ankle: 18-100% stride). Group kinematics differed at the hip (young extension > knee osteoarthritis at 30-47% stride) and ankle (young plantar flexion > older healthy at 62-65% stride). Group-by-tool interactions occurred at the hip (61-63% stride). Significant tool-by-speed interactions were found, with hip and knee flexion increasing more for MoCap than IMU data with speed (hip: 12-15% stride, knee: 60-63% stride). While MoCap- and IMU-derived kinematics differed, our results suggested that the tools similarly detected clinically meaningful differences in gait. Results of the current study suggest that IMU-derived kinematics with OpenSense may enable the valid and reliable evaluation of gait in real-world, unobserved settings.

Trajectory planning of a 4-RR(SS)2 high-speed parallel robot

The trajectory-planning method for a novel 4-degree-of-freedom high-speed parallel robot is studied herein. The robot’s motion mechanism adopts RR(SS)2 as branch chains and has a single moving platform structure. Compared with a double moving platform structure, the proposed parallel robot has better acceleration and deceleration performance since the mass of its moving platform is lighter. An inverse kinematics model of the mechanism is established, and the corresponding relationship between the motion parameters of the end-moving platform and the active arm with three end-motion laws is obtained, followed by the optimization of the motion laws by considering the motion laws’ duration and stability. A Lamé curve is used to transition the right-angled part of the traditional gate trajectory, and the parameters of the Lamé curve are optimized to achieve the shortest movement time and minimum acceleration peak. A method for solving Lamé curve trajectory interpolation points based on deduplication optimization is proposed, and a grasping frequency experiment is conducted on a robot prototype. Results show that the grasping frequency of the optimized Lamé curve prototype can be increased to 147 times/min, and its work efficiency is 54.7% higher than that obtained using the traditional Adept gate-shaped trajectory.

Investigation of negative-parity states in 16C via deuteron inelastic scattering

Two low-lying unbound states in 16C are firstly investigated by the deuteron inelastic scattering in inverse kinematics. Besides the 2- state at 5.45-MeV previously measured in a 1n knockout reaction, a new resonant state at 6.89 MeV is observed for the first time. The inelastic scattering angular distributions of these two states are well reproduced by the distorted-wave Born approximation (DWBA) calculation with an l = 1 excitation. In addition, the spin-parities of the unbound states are discussed and tentatively assigned based on the shell model calculations using the modified YSOX interaction.

Computer Intelligent Algorithm in the Recovery of the Elbow Joint Sports Injury Model

In this study, the inverse kinematics mathematics computer intelligent algorithm model is used to study the sports injuries of the elbow joint of adolescents. At the same time, we simulated the movement parameter changes during the rehabilitation training of the patient’s wrist and proposed a joint angular velocity function based on cubic fitting. Research has found that when the training scene changes greatly or the target task is changed, the smoothness of the elbow joint movement will change. The research conclusions of this article provide a theoretical basis for the selection of man-machine action points and the formulation of rehabilitation training methods. This article establishes the degree-of-freedom simulation model of the operating arm, which is the number of independent position variables in the operating arm, and these position variables determine the positions of all parts in the mechanism.