Forward Kinematics Kernel for Improved Proxy Collision Checking

Many small and large industries use robot arms to establish a range of tasks such as picking and placing, and painting in today's world. However, to complete these tasks, one of the most critical problems is to obtain the desire position of the robot arm's end-effector. There are two methods for analyzing the robot arm: forward kinematic analysis and inverse kinematic analysis. This study aims to model the forward and inverse kinematic of an open-source 4 degrees of freedom (DoF) articulated robotic arm. A kinematic model is designed and further evaluated all the joint parameters to calculate the end-effector's desired position. Forward kinematic is simple to design, but as for the inverse kinematic, a closed-form solution is needed. The developed kinematic model's performance is assessed on a simulated robot arm, and the results were analyzed if the errors were produced within the accepted range. At the end of this study, forward kinematic and inverse kinematic solutions of a 4-DoF articulated robot arm are successfully modeled, which provides the theoretical basis for the subsequent analysis and research of the robot arm.

In this paper, the mechanism and kinematics of the six degree of freedom joint manipulator PUMA560 where contains the forward kinematics, inverse kinematics and trajectory planning problems of PUMA560 are analyzed by the standard D-H method, and the forward and inverse kinematics transformation formula is derived. The manipulator was modeled with Robotics Toolbox, and the forward kinematics, inverse kinematics solutions and trajectory planning were simulated which can obtain the required data in MATLAB. This paper studies the changes of the main kinematic indexes of the robot in the process of operation, which intuitively reflects the motion state of each rod and end working part of the robot, and provides a theoretical basis for the specific development and control strategy of the manipulator.

The complexity of nearest-neighbor search dominates the asymptotic running time of many sampling-based motion-planning algorithms. However, collision detection is often considered to be the computational bottleneck in practice. Examining various asymptotically optimal planning algorithms, we characterize settings, which we call NN-sensitive, in which the practical computational role of nearest-neighbor search is far from being negligible, i.e., the portion of running time taken up by nearest-neighbor search is comparable to, or sometimes even greater than the portion of time taken up by collision detection. This reinforces and substantiates the claim that motion-planning algorithms could significantly benefit from efficient and possibly specially-tailored nearest-neighbor data structures. The asymptotic (near) optimality of these algorithms relies on a prescribed connection radius, defining a ball around a configuration q, such that q needs to be connected to all other configurations in that ball. To facilitate our study, we show how to adapt this radius to non-Euclidean spaces, which are prevalent in motion planning. This technical result is of independent interest, as it enables to compare the radial-connection approach with the common alternative, namely, connecting each configuration to its k nearest neighbors (K-NN). Indeed, as we demonstrate, there are scenarios where using the radial connection scheme, a solution path of a specific cost is produced ten-fold (and more) faster than with K-NN.

A fast and accurate compound collision detector for RRT motion planning

The main objectives of the present work are to model and implement a control system of five degrees of freedom (5 DOF) humanoid arm by using an exoskeleton system with 3 DOF. The exoskeleton system is used to transport the movements of the human’s arm to the controller to control the humanoid arm by using sensors at each target joint to measure the angular displacement of it. To achieve this target, a kinematic analysis of the 5 DOF arm robot has been carried out including the forward, and solving the inverse kinematics. In addition, heterogeneous teleoperation based on forward and inverse kinematic between the humanoid arm and the exoskeleton model has been performed. Also, an experimental set up has been arranged to include the sensors considered (angular displacement sensors), control unit, signal-processing boards, and the actuators (servo motors of the humanoid arm robots). The control experiments have been conducted based on PID control. Keywords : Forward kinematic, inverse kinematic, teleoperation, humanoid robot Cite this Article Elsamanty M, Sayed M, Abdr Aboo S. Heterogeneous Teleoperation Model for Controlling 3D Printed Humanoid Robot Arm with 5 DOF using 3 DOF Exoskeleton. Journal of Control & Instrumentation. 2019; 10(2): 1–15p.

In the Sampling-based motion planning, the collision checking procedure called many times and this operation takes the most planning time. The time spend in the collision checking increases with the number of obstacles. This paper aims to reduce the number of calls of the collision checking procedure in environment containing high number of obstacles. Our approach shows that the complexity of collision checking does not depend on the number of obstacles. The idea is to perform a pre-procedure that localizes the obstacles by segmenting the workspace into a grid and save it in a matrix form. This information is used in the collision checking procedure. We have used the Probabilistic Roadmaps (PRM) motion planner with a punctual robot and polygonal obstacles in 2D environment. Simulation results show the efficiency of our algorithm in reducing the complexity of collision checking and minimizing the planning time.

This present paper focused on the PUMA 560 robot arm's kinematics problem or the connection between angle in each joint and the end-effectors' position. In this paper the Forward and Inverse Kinematic solution of PUMA Robot is solved by analytical approach. All the values of theta are solved by Denavit-Hartenberg analysis (DH). In other words, it deals with finding the homogeneous transformation matrix that describes the position and orientation of the tool frame with respect to the global reference frame. On the other hand, inverse kinematics is used to calculate the joint angles required to achieve the desired position and orientation. The same transformation matrix which resulted from the forward kinematics in order to describe the position and the orientation of the tool frame relative to the robot base frame is used here in the inverse kinematics to solve for the joint angles.

This paper proposes a new kinematic structure of a redundant serial robot arm and presents forward and inverse kinematic analysis. This is a new structure developed based on the robot IRB 2400 of ABB. The new structure consists of six revolute joints and two prismatic joints. The proposed robot arm has only seven degrees of freedom because the structure has a constraint between two revolute joints. Two prismatic joints help to expand workspaces of manipulator from small to very large. The paper describes in details about forward and inverse kinematics. Forward kinematics is derived based on DH Convention while inverse kinematics is calculated based on an objective function to minimize motions of a revolute joint and two prismatic joints. The simulation results on Matlab software indicated that the joint positions and velocities of a redundant serial robot arm matched well the trajectories in Cartesian Space.

Collision-free motion planning allows robots to perform tasks in complex environments, but the conservative bounding curves during collision detection will reduce the robot's dexterity. This paper presents a novel algorithm for real-time motion planning of non-holonomic robots in dynamic scenes. To achieve this, the robot and the obstacles are generally decomposed into a series of superquadric objects. The expanded closed-form Minkowski sums are used to construct the velocity obstacle to deal with the updating orientation of the robot. The algorithm is extended to collision avoidance for different numbers and types of obstacles, which share the same workspace with the robot. We implement our algorithm in various simulations and experiments, where the robot has to avoid collisions with obstacles in real-time. The results demonstrate the effectiveness and efficiency of the proposed algorithm in collision-free motion planning at real-time computation rates and the enhanced dexterity control in complex environments.

In this paper, the possibility of bilateral delta robot with micro-macro control to enhance human ability and transfer experience of operator is considered. Human's hand movement usually occur in three dimension space with high speed and small impendence from hand's mass which is not capable with conventional serial robot that have slow speed and heavy moving part. As a result, parallel delta robot with properties of high speed and light moving part is chosen to suit human's hand behavioral. Micro-macro bilateral or scaling bilateral robot is a robot that scale the position or force from master robot to smaller slave robot. Convectional micro-macro in joint space or motor space bilateral system is not enough to control the task space of the delta robot due to non-linearity of delta robot kinematic. As a result, a micro-macro task space for delta robot in xyz plane by transform joint space into task space using inverse and forward kinematic of delta robot is proposed. Delta robot have rigid body properties which is necessary for detail work and can be considered appropriate micro-macro bilateral manipulator. However, direct kinematics of delta robot have around 40 solutions due to the complexity of pair of spherical joint that may present difficulty in design and manufacturing. Disturbance force is estimated by disturbance observer and scaled by conventional micro-macro method. The experiment and simulation is carry out to verify the proposed method.

To assess the accuracy of reconstructed computed tomography for imaging canine elbow joint spaces. Computed tomography scans of eight cadaveric elbows were obtained and reconstructed computed tomography images were formatted in the dorsal and sagittal planes. Humeroradial and humeroulnar joint space measurements were obtained from these images. Intra-observer and inter-observer variations in joint space measurements were assessed, as was the effect of specimen positioning (inter-image variation). After freezing, four elbows were sectioned in the dorsal plane and four in the sagittal plane. In addition to visual comparison of the frozen sections with reconstructed computed tomography images, joint space measurements were obtained from frozen sections and compared with those from reconstructed computed tomography images. Variation was assessed using statistical calculations and graphical techniques. Both inter-image and intra-observer analyses revealed good agreement and low variation between data sets. Inter-observer correlation was only moderate, though variation was low. Visually, the reconstructed computed tomography images accurately reflected the frozen section anatomy. Agreement between frozen section and reconstructed computed tomography joint space measurements was good, with minimal variation. These results indicate that reconstructed computed tomography is capable of accurately imaging elbow joint spaces and precise joint space measurements can be obtained. Reconstructed computed tomography may be useful for determining joint space measurements and detecting elbow incongruencies in dogs with elbow dysplasia.

In recent years, a number of trajectory optimization algorithms have been proposed and established for motion planning of robot manipulators in complex, but static, predefined environments. To enable reactive motion planning under uncertain conditions caused, for example, by moving obstacles, this paper proposes a formulation of the trajectory optimization problem that is tailored for model predictive control. The proposed algorithmic solution leverages off-the-shelf computational tools for nonlinear model predictive control, optimization, and collision checking. In addition, a motion planning paradigm is introduced to allow for online collision-free motion when following a joystick command. The approach is validated in the context of an industrial pick-and-place application using MATLAB® and a Kinova® robot manipulator, both in simulation and with actual hardware.

Purpose: Inverse Kinematics (I.K.) is not as easy as Forward kinematics (F.K.), where we get a definite result. I.K. algorithm provides several possible solutions. From those finding the best solution is such a critical task. For standard robots which are commercially available in the market, the user is not concerned about I.K.'s complexity. They provide the control board and programming IDE to make it easy. However, when we develop a robotic arm from our D.H. parameter and driver board, complexity arises due to lots of difficulties for executing and successful completion. To make life easy, keeping CoppeliaSim background can eliminate the calculation overhead and get good results. The custom robot is running with less computation power. It may be a good approach. We are using C# for User Interaction. Following step by step, anyone can create a robust I.K. engine with little effort. The complete code is available in GitHub to test and experiment further. Design/Methodology/Approach: The data are propagated through Interprocess communication. For the user interaction, we use visual studio IDE using the most accessible language, C#. The user interaction data are sent to another application, CoppeliaSim, which calculates inverse kinematics, and effective results are displayed through robotic arm movement. Findings/Result: Implementing this procedure can get the excellent result of the robotics arm. Furthermore, by imposing the Value on the real robot, we can get effective results. It minimizes the research overhead on I.K. calculation. Originality/Value: Without knowing I.K. calculation complexity, receiving the Value, we can apply it to the real robot. Two issues we can solve here. One is the calculation, and another one is experiment overhead. Paper Type: Simulation-based Research.

Whole-body motion and footstep planning for humanoid robots with multi-heuristic search

Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions without trying them out in physical reality. Recent progress in fully data-driven self-modeling has enabled machines to learn their own forward kinematics directly from task-agnostic interaction data. However, forward kinematic models can only predict limited aspects of the morphology, such as the position of end effectors or velocity of joints and masses. A key challenge is to model the entire morphology and kinematics without prior knowledge of what aspects of the morphology will be relevant to future tasks. Here, we propose that instead of directly modeling forward kinematics, a more useful form of self-modeling is one that could answer space occupancy queries, conditioned on the robot's state. Such query-driven self-models are continuous in the spatial domain, memory efficient, fully differentiable, and kinematic aware and can be used across a broader range of tasks. In physical experiments, we demonstrate how a visual self-model is accurate to about 1% of the workspace, enabling the robot to perform various motion planning and control tasks. Visual self-modeling can also allow the robot to detect, localize, and recover from real-world damage, leading to improved machine resiliency.