{"id":48,"date":"2009-03-06T03:07:11","date_gmt":"2009-03-06T03:07:11","guid":{"rendered":"https:\/\/blogs.mathworks.com\/seth\/2009\/03\/06\/models-inspired-by-real-life\/"},"modified":"2016-08-29T14:18:46","modified_gmt":"2016-08-29T19:18:46","slug":"models-inspired-by-real-life","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/simulink\/2009\/03\/06\/models-inspired-by-real-life\/","title":{"rendered":"Models Inspired by Real Life"},"content":{"rendered":"

Often models are the predecessor to a real-life device; however, sometimes a device inspires the model. In the 1980s, there was a group known as the Leg Lab at CMU who researched running robots.\u00a0 In 1986 the Leg Lab moved to MIT.\u00a0 Some of their robots are now on display at the MIT Museum<\/a>, and they still inspire wonder in visitors today.\u00a0 One of those robots is a 3-D One-Legged Hopper<\/a> which inspired my colleague, Guy Rouleau<\/a>.<\/p>\n

I saw this robot at the MIT Museum last winter and after discussing with few colleagues at The MathWorks we decided that it would be cool to have a Simulink model of this robot.<\/quote><\/p>\n

Read on to learn about how Guy constructed and controlled this one-legged hopper<\/a> (download from the file exchange).<\/p>\n

\"2-D<\/p>\n

Simulation and Control of a One-Legged Hopping Robot<\/strong><\/p>\n

By Guy Rouleau<\/p>\n

\"Robot<\/p>\n

Here is the description of a one-legged hopping robot Simulink model I completed recently. I will explain how I prepared and implemented this simulation.<\/p>\n

Preparation<\/strong><\/p>\n

Before modeling any system in Simulink, it is always good to have a plan. To begin I always like to draw a simple representation of the system I want to model. In this picture we see two bodies (let\u2019s call them body<\/strong> and leg<\/strong>) connected together at the hip. The robot has two actuated degrees of freedom (DoF) in his configuration space, the angle between the body and the leg, and the length of the leg. These 2 DoF will be used to control the 3 DoF motion of the body in space (height, distance and angle).\u00a0<\/p>\n

\"Hopping<\/p>\n

Now that the robot is described, it is time to think about how to control it. The robot control can be divided into three independent controllers:<\/p>\n

    \n
  1. Attitude Control - <\/strong>The length of the leg is controlled by a pneumatic actuator. This actuator behaves like a spring. It gives a smooth
    \n landing and injects force to keep the robot bouncing.<\/li>\n
  2. Velocity Control \u2013 <\/strong>As when a person walks, the leg is brought in front of the body while it is in the air. While the leg touches the ground, then the body is brought in front.<\/li>\n
  3. Orientation Control - <\/strong>During the stance, the leg is in contact with the ground. A torque is applied at the hip to control the angle of the body.<\/li>\n<\/ol>\n

    The following picture shows the three controllers graphically:<\/p>\n

    \"The<\/p>\n

    Now I have a good idea of what to implement, it is time to have fun and play with Simulink. For this model, SimMechanics is the most appropriate Blockset to
    \nmodel the robot.<\/p>\n

    Implementation<\/strong><\/p>\n

    When I begin a SimMechanics model for a moving robot, I like fixing the position of the body in space. By doing so, I can verify if the configuration of the
    \nactuators behaves as expected. This SimMechanics model looks like this:<\/p>\n


    \n \"SimMechanics
    \n<\/a><\/p>\n

    Using this model I can test different inputs and see the resulting motion at the tip of the leg. Once I am satisfied with this motion, I can think about the interaction with the ground. <\/p>\n

    My new goal is now to see the robot falling from a certain initial eight, bouncing a few times and fall. To model the ground, I use the Bouncing Ball demo provided with SimMechanics. After grouping components within subsystems, the model now looks like the following picture.<\/p>\n


    \n
    \n<\/a><\/p>\n

    Once the contact forces and robot motion are validated, it is time to implement the control architecture. <\/p>\n

    Typically, when I implement a controller I like to divide the model in the following subsystems:<\/p>\n

    Sensor modeling<\/strong><\/p>\n

    This subsystem extracts and processes the information from the SimMechanics model to generate signals that could be provided by real sensors. For the hopping robot, I will measure the following:<\/p>\n