In this paper, we propose an alternative motion planning method for a wearable robot with a variable stride length and walking speed. Trajectories are planned in a joint space rather than a workspace ...to avoid an ill-posed problem with no solution in inverse kinematics, and to consider the joint's range of motion, maximum velocity, foot clearance, and backward balance. The joint trajectories are represented by minimum jerk trajectories. Two via-points are assigned, and the parameters (angle and angular velocity) at the via-points are determined by applying an inverted pendulum model or optimization to satisfy the constraints. The fastest gait pattern generated by the proposed algorithm was twice as fast as the pattern generated by the workspace-based planning method. We confirmed that the fastest walking pattern of 0.36 m/s was feasible on a treadmill, and a walking pattern of 0.27 m/s was found for walking across the floor with a walker. Furthermore, the proposed method required approximately 65% of the electric power for the workspace-based method for the same walking speed and stride length. These results suggest that the proposed motion planning method is effective at generating a high-speed and efficient gait pattern for a wearable robot.
Purpose
This paper aims to deal with the human activity recognition using human gait pattern. The paper has considered the experiment results of seven different activities: normal walk, jogging, ...walking on toe, walking on heel, upstairs, downstairs and sit-ups.
Design/methodology/approach
In this current research, the data is collected for different activities using tri-axial inertial measurement unit (IMU) sensor enabled with three-axis accelerometer to capture the spatial data, three-axis gyroscopes to capture the orientation around axis and 3° magnetometer. It was wirelessly connected to the receiver. The IMU sensor is placed at the centre of mass position of each subject. The data is collected for 30 subjects including 11 females and 19 males of different age groups between 10 and 45 years. The captured data is pre-processed using different filters and cubic spline techniques. After processing, the data are labelled into seven activities. For data acquisition, a Python-based GUI has been designed to analyse and display the processed data. The data is further classified using four different deep learning model: deep neural network, bidirectional-long short-term memory (BLSTM), convolution neural network (CNN) and CNN-LSTM. The model classification accuracy of different classifiers is reported to be 58%, 84%, 86% and 90%.
Findings
The activities recognition using gait was obtained in an open environment. All data is collected using an IMU sensor enabled with gyroscope, accelerometer and magnetometer in both offline and real-time activity recognition using gait. Both sensors showed their usefulness in empirical capability to capture a precised data during all seven activities. The inverse kinematics algorithm is solved to calculate the joint angle from spatial data for all six joints hip, knee, ankle of left and right leg.
Practical implications
This work helps to recognize the walking activity using gait pattern analysis. Further, it helps to understand the different joint angle patterns during different activities. A system is designed for real-time analysis of human walking activity using gait. A standalone real-time system has been designed and realized for analysis of these seven different activities.
Originality/value
The data is collected through IMU sensors for seven activities with equal timestamp without noise and data loss using wirelessly. The setup is useful for the data collection in an open environment outside the laboratory environment for activity recognition. The paper also presents the analysis of all seven different activity trajectories patterns.
In this paper, an improved mathematical model for a novel hyper redundant hybrid mechanism with 12 DOFs is presented. This hyper redundant hybrid mechanism is composed sequentially of two Stewart ...platforms as slave and master modules known as 2 (6-Universal-Prismatic-Spherical). Regarding to the redundancy of this mechanism, a complex trajectory is considered for this redundant mechanism which is impossible for non-redundant parallel mechanisms to navigate. First, the inverse kinematics of mechanism is solved and Jacobian matrices are obtained considering the rotational DOF for pods around axial direction. Next, using energy principles and Lagrange method the exact equation of motion is formed. Finally, to verify the results obtained by simulation, an experiment on 2-(6UPS) mechanism is carried out to validate the results. According to the results, it is obvious that the proposed mathematical model is comprehensive, and it can be used with great reliability for all intentions such as control strategies.
Estimating kinematics from optical motion capture with skin-mounted markers, referred to as an inverse kinematic (IK) calculation, is the most common experimental technique in human motion analysis. ...Kinematics are often used to diagnose movement disorders and plan treatment strategies. In many such applications, small differences in joint angles can be clinically significant. Kinematics are also used to estimate joint powers, muscle forces, and other quantities of interest that cannot typically be measured directly. Thus, the accuracy and reproducibility of IK calculations are critical. In this work, we isolate and quantify the uncertainty in joint angles, moments, and powers due to two sources of error during IK analyses: errors in the placement of markers on the model (marker registration) and errors in the dimensions of the model's body segments (model scaling). We demonstrate that IK solutions are best presented as a distribution of equally probable trajectories when these sources of modeling uncertainty are considered. Notably, a substantial amount of uncertainty exists in the computed kinematics and kinetics even if low marker tracking errors are achieved. For example, considering only 2 cm of marker registration uncertainty, peak ankle plantarflexion angle varied by 15.9°, peak ankle plantarflexion moment varied by 26.6 N⋅m, and peak ankle power at push off varied by 75.9 W during healthy gait. This uncertainty can directly impact the classification of patient movements and the evaluation of training or device effectiveness, such as calculations of push-off power. We provide scripts in OpenSim so that others can reproduce our results and quantify the effect of modeling uncertainty in their own studies.
This paper presents Batch OpenSim Processing Scripts (BOPS), a Matlab toolbox for batch processing common OpenSim procedures: Inverse Kinematics, Inverse Dynamics, Muscle Analysis, Static ...Optimization, and Joint Reaction Analysis. BOPS is an easy-to-use and highly configurable tool that aims to reduce the time required to process large datasets, thus fostering the adoption of musculoskeletal modeling and simulations in daily practice. Its graphical user interface includes pre-defined setup files and has been designed to fulfill the needs of different research projects by simplifying the customization of the procedures, facilitating the analysis, and boosting research group collaborations. BOPS is released under Apache License 2.0, and its source code is freely available on SimTK and GitHub.
With the progress of 3D human pose and shape estimation, state-of-the-art methods can either be robust to occlusions or obtain pixel-aligned accuracy in non-occlusion cases. However, they cannot ...obtain robustness and mesh-image alignment at the same time. In this work, we present NIKI (Neural Inverse Kinematics with Invertible Neural Network), which models bidirectional errors to improve the robustness to occlusions and obtain pixel-aligned accuracy. NIKI can learn from both the forward and inverse processes with invertible networks. In the inverse process, the model separates the error from the plausible 3D pose manifold for a robust 3D human pose estimation. In the forward process, we enforce the zero-error boundary conditions to improve the sensitivity to reliable joint positions for better mesh-image alignment. Furthermore, NIKI emulates the analytical inverse kinematics algorithms with the twist-and-swing decomposition for better interpretability. Experiments on standard and occlusion-specific benchmarks demonstrate the effectiveness of NIKI, where we exhibit robust and well-aligned results simultaneously. Code is available at https://github.com/Jeff-sjtu/NIKI.
Most existing studies on manipulator focus on the field of teaching and research. Other manipulators used for industrial production also have several disadvantages, including high cost, complicated ...control and low flexibility. Accordingly, in this paper, a simple automatic grabbing method of manipulator is proposed based on monocular ranging. The method is developed via the openmv vision platform. First, the target object is identified in the lens, the linear distance of the lens from the target object is calculated through monocular ranging, and then the inverse kinematics of the manipulator is exploited to calculate the rotation angle of each steering engine. Next, the contradiction between system speed and impact is balanced using the five-time curve trajectory optimization algorithm. The results of tests suggest that the method can achieve accurate capture of the target object in the grab range. The method, compared with the teaching and even the engineering manipulator system, is characterized by lower cost, simple and flexible control. Besides, it can be used to implement simple tasks in industry.
Chronic immobility brings health complications on a wide spectrum of pathologies. Patients on these conditions daily need assistance, especially bedridden, and with neuromuscular disorders, which may ...contain rehabilitation activities to, hence, improve the partial or full recovery of their mobility. Sessions that promote aerobic exercises are still the most recommended therapies. This article proposes an embedded electronic board (EEB) as an open development system oriented to help in fastening the automation of prototypes and medical robotics applications. EEB contains a microcontroller with peripherals that permit sensor data acquisition, manipulate actuators commonly used on medical devices, and being interfaced with computers that may contain customized graphical user interface (GUI). Three test sets have been conducted to validate the reliability of the inverse kinematics and convenience on the automation improvement to obtain current demand by channel and check electrical integrity. An experiment to see the temperature variation on human face, due to an infrared sensing, compared with gradually changing the position of the body has been carried out. Results show an accuracy on the long run of activity with 99.0% and 99.7% on 400- and Formula Omitted-mm stroke actuators without recalibration components; the face-based infrared sensing, in conjunction with movements, has demonstrated to be an excellent monitoring for detecting the eye vascularization in the effort to display eventual cardiac abnormalities. This is the first time for this kind of approach. Results have increased the automation capabilities of the bed, offering new features that enhance its fields of application together with significant economic savings.
In this paper, an optimal collision‐free trajectory is developed based on the hybrid optimization algorithms for industrial robotic manipulators (IRMs). Three IRMs such as PUMA 560 (six degrees of ...freedom—6DOF), KUKA LBR iiwa 14 R820 (7DOF), and ABB IRB 140 (6DOF) are considered. The key objective is to enhance the smoothness and efficiency of manufacturing robots by optimum joint trajectory design using the seventh‐order polynomial function. The proposed approach is to solve both kinematics and trajectory planning problems by using the different combinations of the hybrid meta‐heuristic algorithms. The kinematic parameters including jerk, acceleration, and velocity mostly impact the travel smoothness of the robot end‐effector on the trajectory path. Therefore, these parameters are to be constrained for generating the collision‐free path. The endurance of velocity and acceleration can be obtained by reducing the jerk which leads to smooth robotic motion. The proposed work is executed using a robotic toolbox in MATLAB with a graphical user interface. The values of acceleration, velocity, and jerk are computed for the robot joints. Each robot obtained the minimum traveling time for without and with an obstacle which is 0.0118 and 0.0313 s for PUMA and 0.0117 and 0.0310 s for KUKA, and 0.0114 and 0.0120 s for ABB IRB 140 robot. From the experimental outcomes, the proposed scheme of the hybrid optimization algorithms is more effective for the trajectory planning of IRMs than that of other works.
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