Modeling, Evaluation, and Control Optimization of Exosuit with OpenSim

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This project is motivated by DARPA Warrior Web Program.

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• There has been a lot of research into exoskeletons over the years to alleviate heavy loads that soldiers carry, but strapping a person into a robotic outfit just isn't practical in a combat zone yet.

• DARPA's Warrior Web program aims to build a lightweight suit that improves a soldier's endurance and overall effectiveness, while preventing injuries.

• The main goals by developing the warrior web are:

• You can see the details of this project on http://www.darpa.mil/Our_Work/DSO/Programs/Warrior_Web.aspx.

In order to develop an under-suit that doesn’t hinder the wearer’s free movement, researchers are trying to make it soft and deformable, but still capable of applying force to body joints. The Harvard exosuit is an example of a new approach to creating an under-suit in a soft and deformable manner.

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• Experimental data proved that it can help loaded walking by reducing metabolic cost.

• This suit applies force to lower limb joints through cables driven by actuators in the backpack.

As the exosuit tries to assist human gait with a deformable structure, there are many challenges in its development. The challenges are:

• It is difficult to analyze the effectiveness of the suit.

• It is difficult to find the optimal input force for actuators to reduce the metabolic cost.

• It is difficult to identify the effect of changes in design parameters.

The reasons for the challenges are:

• The suit is deformable and closely attached to the body.

• We cannot predict how external actuation assists muscles during loaded walking, as the human body is highly redundant.

• Experimental data is inconsistent case-by-case.

This project attempts to tackle the challenges of developing a wearable device for supporting loaded gait with OpenSim simulations. Simulation can help develop the wearable device, as it can give an intuition on how the device helps muscles and how metabolic cost changes during loaded walking. We can also find the key features that one should account for in order to make the device more efficient. I hope this project will provide a systematic way of analyzing and designing a soft wearable device. The initial goals of this project are:

• Evaluate the effectiveness of wearing active actuators on metabolic cost reduction.

• Explain how the exosuit can help loaded gait.

• Verify the impact of changes in design parameters.

• Find optimal control inputs for active actuators.

• Two sets of data were collected from the same subject:

• The subject didn't wear a suit and walked freely.

• Walking speeds were identical.

• Mass of the load was 38 kg.

To simulate the movement of the exosuit wearer, the first thing to do is to create a model which can replicate a real subject as realistically as possible. Before I created the simulation model with active actuators on it, I used the generic gait model to go through the basic steps in the OpenSim simulation pipeline. By doing so, I could make my model dynamically consistent to the experimental data. I then added actuators and metabolic cost probes to the model.

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The diagram above describes the procedure used to simulate the generic gait model.

• The first three steps comprise the basic modeling procedure in OpenSim to make a model dynamically and kinematically consistent with the experimental data. For more information, see the following pages on Confluence:

• After step 3 was complete, probes for calculating metabolic cost were added to the model. For more information about how to add the probes, see Simulation-Based Design to Reduce Metabolic Cost.

• Finally, I added active actuators to the model. Here, I used the PathActuator class to simulate the active actuators of the exosuit, as they are cable-driven actuators. If you are interested in how the PathActuator works, see OpenSIm::PathActuator Class.

Here are the figures of sample simulation models. I modified the RRA-adjusted model to create several different types of models for comparison.

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Three types of models were created for loaded gait simulations:

• A model without any additional actuators

• A model with path actuators supporting plantarflexion

• A model with path actuators supporting hip extension

The path actuator supporting plantarflexion is attached to the heel and tibia, and the path actuator supporting hip extension is attached to the backpack and femur. For simplicity, the loaded mass was added directly to the torso.

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The same types of models were created for unloaded gait simulations.

The idea to optimize the control input force for the actuators is to take advantage of the Computed Muscle Control (CMC) tool. The main reason we use CMC in OpenSim is to find the most suitable excitations for muscles to create body movement while minimizing muscle activations. To see how it works, see How CMC Works.

In this project, I make different use of the optimization process in CMC in order to optimize the control input force for active actuators.

• CMC procedure is static optimization process, and it minimizes the cost function J which can be represented as  

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• When we add active actuators to an OpenSim model, the activation term in the cost function becomes 

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• Now, if we diminish the influnece of X_actuator on J and run CMC, the optimizer tries to find X_actuator in the manner of minimizing muscle activations.

• We know that minimizing muscle activation correponds to minimizing metabolic cost, so we can conclude that the actuator input force resulting from CMC if we diminish the influence of X_actuator on objective function J is the optimal actuator input for metabolic cost reduction.

• Muscle force is constructed from the equation F_actuator =  F_actuator^max * X_actuator. If we assign a large maximum force to each actuator, the actuator control X_actuator decreases, so the influence of the actuator on J is decreased.

• Using this idea, I found an optimal input for each actuator, and also found the metabolic cost reduction after running CMC with a model where active actuators were added.