- Modeling and Simulation of Walking Robots
- Robotics System Toolbox
- Robotics System Toolbox
- Humanoid Robot
- Developing Advanced Control Software for the iCub Humanoid Robot

## Modeling and Simulation of Walking Robots

Updated 06 Dec MathWorks Student Competitions Team Retrieved April 9, I also have the problems of unrecognized function or variable 'robotParameters' but I have already run the startupWalkingRobot script. So what's going wrong? Thanks a lot! Jingchao, I think you need to disable the "useParallel" flag in the script if you want to see the simulation animations, since that Mechanics Explorer doesn't support parallel execution. Sebastian-- Hello Sebastian, When running the example of reinforcement learning, I can't see the animation demonstration of the learning process. How should I set this up? Thank you. Lars: Feel free to email us at roboticsarena mathworks. I cant seem to view the Models. It gives an error when I try to look at it or it doesn't show at all. Jorge -- did you run the startupWalkingRobot script to add all the folders to the path? I also get this problem with the file step4. Can any one help me with this what im doing wrong ,thank you. Hello First of all thanks for your lectures I have a error. Can you tell what is wrong. The basic files are developed in Ra. For earlier versions, you can change your Simulink preferences to load models in later versions and see whether it works on your end. Can you please upload the Ra model of the same? Hey, could you please send the file version which is compatible with matlab a?## Robotics System Toolbox

Documentation Help Center. This example shows how to derive analytical solutions for the inverse kinematics of the head chain of a humanoid robot. Describe the kinematics of the head-chain link the link between the torso and the head of the NAO humanoid robot [1] using the Denavit-Hartenberg DH parameters and notations based on a study by Kofinas et al. The following transformation defines the head-chain link. A B a s e0 is the translation from the base torso to the joint or reference frame 0. T 01 is the orientation of reference 1 relative to 0. T 12 is the orientation of reference 2 relative to 1. R x is the roll rotation. R y is the pitch rotation. A 2H e a d is the translation from reference 2 to the end-effector point the head. T 1 : 34 defines the coordinates of the head, which are x cy cz c. In this example, you analytically solve the inverse kinematics problem by returning all orientations of individual joints in the head-chain link given head coordinates of xcycand zc within the reachable space. Then, you convert the analytical results to purely numeric functions for efficiency. Solving analytically when doing so is possible lets you perform computations in real time and avoid singularities, which cause difficulty for numerical methods. The function getKinematicChain returns the specific kinematic chain for the NAO robot in terms of symbolic variables. For details on getKinematicChainsee the Helper Functions section. Define the individual matrices as follows. The robot can then achieve the desired position xcyczc. Although you can see these parameters in the transformation matrices, they do not exist as variables in the MATLAB base workspace. This is because these parameters originate from a function. Functions do not use the base workspace. Each function workspace is separate from the base workspace and all other workspaces to protect the data integrity. Thus, to use these variables outside of the function getKinematicChainuse syms to create them. Simplify the left and right sides of the equation, and define equations of interest matching the expressions for coordinate positions. However, the equations also imply that you cannot arbitrarily choose xcycand zc. Therefore, also consider yc as a variable. All other unknowns of the system are symbolic parameters. This example follows a typical algebraic approach for solving inverse kinematics problems [3]. The idea is to get a compact representation of the solution, where the expression of each variable is in terms of parameters and variables for which you already solved the equations. Then, express the other variable in terms of the known variable and parameters.

## Robotics System Toolbox

Convert your robotics ideas and concepts into autonomous systems that work seamlessly in real-world environments. Robotics researchers and engineers use MATLAB and Simulink to design and tune algorithms, model real-world systems, and automatically generate code — all from one software environment. Design and analyze 3D rigid-body mechanics such as vehicle platforms and manipulator arms and actuator dynamics such as mechatronic or fluid systems. Add constraints, such as friction, and model multi-domain systems with electrical, hydraulic, or pneumatic, and other components. Once in operation, reuse design models as digital twins. You can connect to sensors through ROS. You can automate common sensor processing workflows such as importing and batch-processing large data sets, sensor calibration, noise reduction, geometric transformation, segmentation, and registration. Built-in MATLAB apps let you interactively perform object detection and tracking, motion estimation, 3D point-cloud processing, and sensor fusion. Use deep learning for image classification, regression, and feature learning using convolutional neural networks CNNs. You can use algorithms and apps to systematically analyze, design, and visualize the behavior of complex systems in time and frequency domains. Automatically tune compensator parameters using interactive techniques such as bode loop shaping and the root locus method. You can tune gain-scheduled controllers and specify multiple tuning objectives, such as reference tracking, disturbance rejection, and stability margins. Code generation and requirements traceability helps you validate your system and certify compliance. That integration reduces overall project development time and the chances of introducing errors. With personalized coaching and a fully transparent approach, our goal is to leave you in control of your improved processes, tools, and design work. We will not sell or rent your personal contact information. See our privacy policy for details. Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select:. Select the China site in Chinese or English for best site performance. Other MathWorks country sites are not optimized for visits from your location. Toggle Main Navigation. Robotics and Autonomous Systems. Search MathWorks. Overview Resources. Connect to a range of sensors and actuators so you can send control signals or analyze many types of data. Connect to low-cost hardware such as Arduino and Raspberry Pi using pre-built hardware support packages. Simplify design reviews by creating shareable code and applications.

## Humanoid Robot

First, you will learn how to model the rigid-body mechanics of a walking robot using Simscape Multibody. You will also see how to model physical contact between the feet and ground. Then, you will explore how to trade off various levels of model fidelity for the joint actuators and controllers. Contact Modeling with Simulink Sebastian Castro and Ed Marquez Brunal introduce the fundamentals of mechanical contact modeling and simulation with Simulink, as well as show examples for automotive and robotics applications. Contact Modeling with Simscape Sebastian Castro and Ed Marquez Brunal discuss various approaches and online resources for modeling mechanical contact and friction forces using Simulink, Simscape, and Simscape Multibody. Zachary Leitzau from Embry-Riddle Aeronautical University demonstrates the use of a self-built app to help design a model airplane. Designing Robot Manipulator Algorithms Accelerate the design of robot manipulator algorithms by using the Robotics Systems Toolbox functionality and integrating robot models with simulation tools to program and test manipulation tasks. System Identification of Blue Robotics Thrusters Create a model for a piece of hardware from input and output data using the System Identification app. Connell D'Souza and Kris Fedorenko explain the workflow from data gathering to model evaluation. Labeling Ground Truth for Object Detection Use the Ground Truth Labeler app to generate quality ground truth data that can be used to train and evaluate object detectors. Training and Validating Object Detectors Use labeled ground truth data to train and evaluate object detectors. Simulating Pneumatic Robot Actuators Veer and Maitreyee show how you can model a pneumatic system by using physical blocks available in Simscape. Simulating Robot Throwing Mechanisms Veer and Maitreyee show you how to build a throwing mechanism to throw a ball at a certain target using Simscape Multibody. Control Design for Robot Throwing Systems Veer and Maitreyee first show how you can extend Simscape Multibody throwing mechanism models with physical effects modeled in Simscape. Later, controller is implemented in the system to track the reference piston position. Modeling and Simulation of Walking Robots Learn how to model a bipedal walking robot using Simscape, including physical contact forces, actuator models, and controllers. Data Preprocessing for Deep Learning. Multibody Simulation with Simscape Multibody. Modeling a Scissor Jack. Modeling an Aileron. Modeling Contact Forces in a Geneva Drive. Modeling Contact Forces in a Cam Follower. Modeling an Engine. Modeling a Piston. Physical Modeling: Building a Rotary Pendulum. Hybrid Electric Vehicle Modeling and Simulation. Modeling and Simulation of a Sidewall Coring Tool. Modeling and Simulation Made Easy with Simulink. Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select:. Select the China site in Chinese or English for best site performance.

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