...
| Section |
|---|
...
Team Member
- Jaehyun Bae
Overview
|
...
|
Motivation
DARPA Warrior Web Program
This project is motivated by DARPA Warrior Web Program.
- There has been a lot of research into exoskeletons over the years to alleviate heavy loads that soldiers should burdencarry, 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:
- To prevent and reduce musculoskeletal injuries.
- To augment positive work done by the muscles and reduce the physical burden.
- You can see the details of this project on http://www.darpa.mil/Our_Work/DSO/Programs/Warrior_Web.aspx.
Harvard Exosuit
In order to develop an under-suit that doesn’t interrupt hinder the wearer’s free movement, researchers are trying to make it soft and deformable, but still capable of applying force to body joints. Among several different projects in the Warrior Web program, I focused on Harvard exosuitThe Harvard exosuit is an example of a new approach to creating an under-suit in a soft and deformable manner.
...
- Experimental data proved that it can help loaded walking by reducing metabolic costscost.
- This suit applies force to lower limb joints through cables driven by actuators in the backpack.
...
Challenges
As it is a new approach the exosuit tries to assist human gait with a deformable structure, there are many challenges while developing the exosuitin its development. The examples of the challenges are:
- It is difficult to analyze the effectivness effectiveness of existthe 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 change of changes in design parameters.
The reasons for the challenges are:
- The under-suit may be soft and deformable Hard to identify
- suit is deformable and closely attached to the body.
- We cannot predict how external actuation assists loaded gaitmuscles during loaded walking, as the human body is highly redundant.
- Experimental metabolic cost data is inconsistent case-by-case.
Goals
...
...
...
...
...
...
...
...
...
- Evaluate the effectiveness of wearing active actuator actuators on metabolic cost reduction during loaded walking.
- Explain how the exosuit can help loaded gait.
- Verify the impact of changes in design parameters.
- Find optimal control inputs for exosuit active actuators.
- Evaluate the effectiveness of Biarticular actuator
Strategy
Experimental data
- Two
...
- sets of data were collected from
...
- the same subject
...
- :
- One gait cycle of loaded walking (
...
- from left toe-off to next left toe-off).
- One gait cycle of unloaded walking (
...
- again, from left toe-off to next left toe-off)
...
For both data, walking speed is identical, and mass of the load for loaded walking was 38kg.
- Data type
- Marker position data
- Ground reaction force data
- Subject
- mass: 61.3kg
- Sex: male
Modeling
...
- .
- The subject didn't wear a suit and walked freely.
- Walking speeds were identical.
- Mass of the load was 38 kg.
Modeling
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 as we can. In this project, as the experimental data was acquired from a subject walking freely, it is not possible to make a realistic exosuit wearer. However, to . 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, my model was gone through the basic steps of modeling procedure in Opensim, and . I then added actuators and metabolic cost probes to the model.
...
Modeling a subject wearing an active actuator
The diagram above describes what procedure my model had gone throughthe procedure used to simulate the generic gait model.
- The first three steps are comprise the basic modeling procedure in Opensim OpenSim to make a model dynamically and kinematically consistent to with the experimental data. For more information, refer tosee the following pages on Confluence:
- After RRA is done to the modelstep 3 was complete, probes for calculating metabolic cost were added to the model. . For more information about how to add the probes, refer tosee Simulation-Based Design to Reduce Metabolic Cost.
- And thenFinally, 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 actuatoractuators. If you are interested in how the PathActuator works, refer tosee OpenSIm::PathActuator Class.
Sample models
Here are the figures of sample simulation models. I created modified the RRA-adjusted model to create several different types of models for both loaded gait and unloaded gaitcomparison.
Loaded gait model
Three different 
Loaded gait models
Three types of models were created for loaded gait simulationsimulations:
- A model without actuatorany additional actuators
- A model with path actuators supporting plantar flexionplantarflexion
- A model with path actuators supporting hip extension
The path actuator supporting plantar flexion plantarflexion is attached to the heel and tibia, and the pathactuator path actuator supporting hip extension is attached to the backpack and femur. Loaded For simplicity, the loaded mass was added directly to the torso for simplicity.
Unloaded gait
...
...
models
The same types of models were created for unloaded gait simulation. The main difference between loaded gait model and unloaded gait model is the mass of torso, and transparancy of backpack.simulations.
Optimization methodology
The idea to optimize the control input force for the actuator actuators is to take advantage of the Computed Muscle Control (CMC) tool. The main reason we use CMC in OpenSim is to find a the most suitable excitations for muscles to create body movement while minimizing activationmuscle activations. To see how it works, refer tosee How CMC Works.
In this project, I make use of different use of the objective function optimization process in CMC in order to find optimal optimize the control input force for active actuators.
CMC procedure
containsis static optimization process, and it
tries to minimizeminimizes the cost function J which can be represented
asas
Mathblock J = \sum_{i=1}^{n_x} x_i^2 + \sum_{j=1}^{n_q} w_j \left( \ddot{q}_j\,^* - \ddot{q}_j \right)^2
When we add active actuators
onto an OpenSim
Modelmodel, the activation term in
cost function becomesWhere X_the cost function becomes
Mathblock x = \begin{bmatrix} x_{\mathrm{muscle}} \\ x_{\mathrm{actuator}} \end{bmatrix}
where Xmuscle is muscle control and X
...
actuator is actuator control. As X
...
actuator is part of activation
...
states,
...
it is also adjusted after the optimization process.
- Now, if we diminish the influnece of X_actuator on on J , and run CMC, the optimizer tries to find X_actuator in order to minimize muscle activationthe manner of minimizing muscle activations.
- We know that minimizing muscle activation correponds to minimizing metabolic cost, so we can we can say conclude that the actuator input force resulted resulting from CMC after diminishing if we diminish the influence of X_actuator on objective function J is the optimal actuator input for most efficient metabolic cost reduction.
- Muscle force is constructed by from the equation
...
- Factuator = Factuatormax * Xactuator. If we assign a large
...
- maximum force to each actuator,
...
- the actuator control
...
- Xactuator
...
- decreases, so
...
- the influence of the actuator
...
- on J is
...
- decreased.
- Using this methodologyidea, I could find found an optimal input for each actuator, and also see found the metabolic cost reduction after running CMC with a model where active actuators are were added to a model.
...
Results and Discussion
Metabolic cost change when active actuators are added to the model
I investigated how much metabolic cost is reduced when active actuators are added to a model, and optimal input force is applied to a model by active actuators. I did simulation for simulated both loaded and unloaded walking cases, and I compared the influence of the hip actuator and ankle actuator to actuators on metabolic cost reduction.I assigned I used 10,000N to 000 N as the maximum active actuator force in order to find optimal control input force through CMC(Factuatormax) for these simulations.
| Loaded walking | Unloaded walking | ||||||||
|---|---|---|---|---|---|---|---|---|---|
|
|
 |
 |
- Metabolic cost reduction when active actuators are added to the loaded gait model:
- Ankle actuator: 10.35%
- Hip actuator: 6.62%
- Metabolic cost reduction when active actuators are added to the unloaded gait model:
- Ankle actuator: 10.62%
- Hip actuator: 1.04%
- Things to notice:
- The metabolic cost is much lower during unloaded walking than loaded walking. Loaded Unloaded walking costs only 75% of the metabolic energy compared to spent during loaded walking.
- Ankle The ankle actuator works better to reduce at reducing metabolic cost than the hip actuator when we can apply the optimal input force.
- Hip The hip actuator is not assistive to during unloaded gait.
Therefore, we can say that the ankle actuator helps reduce metabolic cost reduction better than the hip actuator if we have an optimal actuator which has ideal actuators with no maximum force limitation.
Optimal actuator input force
| Loaded walking | Unloaded walking | |
|---|---|---|
| Ankle actuator |   |   |
| Hip actuator |   |   |
Optimal input force for Ankle the ankle actuator:
- Actuation is started begins right after the toe-off of a the foot on the opposite side, and the peak force occurs 7.12% of gait cycle before toe off, and ends at the happens between heal-strike of the foot on the opposite side and toe-off of a the foot on the same side.
- This The same actuation scheme strategy is valid for both loaded gait and unloaded gait.
- This The force signal is clear and easy to implement in the real world.
- However, the maximum actuation force is about 2500 N, which is too high to achieve in reality.
Optimal input force for Hip the hip actuator:
- Hip The hip actuator can reduce the metabolic cost with lower maximum force than the ankle actuator.
- However, it is hard to identify how the actuator assists walking.
- Also, it is difficult to implement the optimal control input for the hip actuator in the real world
...
- .
How the ankle actuator
...
assists loaded gait
We can explain how the optimal actuation input for the ankle actuator could help helps loaded gait by investigating the change of plantar flexor plantarflexor muscle forces.
...
- The gastrocnemius muscle forces are barely changedchange.
- Other plantarflexor muscle forces, including Soleus soleus muscle forces, are significantly decreased.
- If we draw compare the active actuator input force with the sum of the baseline uniarticular forces and active actuator input force together, we can see that the active actuator force follows the sum of the baseline uniarticular muscle forces.
...
Optimal input force for ankle actuator
...
when actuation force is limited to
...
400 N (i.e., realistic actuation limit)
- From the previous results, we found that the optimal input force for the hip actuator is small enough to be achieved by a real actuator, while the optimal input force for ankle actuator is not
- realistic (> 2000 N). Therefore, I tried different types of input forces for ankle actuators up to
- 400 N, and
- compared the results to the optimal control input case.
- My initial guess was to saturate the optimal input force that I found earlier at
...
- 400 N. I generated an new input force which is identical to the optimal input force up to
...
- 400 N, and saturated once the optimal input force
...
- exceeded 400 N.
- The second input force I tried was a new result from my CMC simulations. The new CMC result was acquired by assigning 4000 N to the maximum actuation force and bounding the control input between 0 and 0.1.
...
- In other
...
- words,
...
| Mathblock |
|---|
F_{\mathrm{actuator}}^{\mathrm{max}} = 400 N, \quad 0 \leq x_{\mathrm{actuator}} \leq 0.1 |
According to the formula Factuator = Factuatormax * Xactuator, the new CMC
...
result also has a maximum force of
...
...
400 N. As Xactuator is bounded between 0 and 0.1 and Xmuscle is chosen between 0 and 1, the influence of Xactuator to the objective function of the CMC procedure is relatively lower than that of Xmuscle, so we can use this idea to create an optimal input for the ankle actuator when the maximum actuation force is limited.
When we compare the saturated optimal input and the result from the new CMC procedure, we find similarity. Now, let's compare the metabolic cost reduction when each control input is applied to ankle actuators.
Metabolic cost reduction
| Loaded walking | Unloaded walking |
|---|---|
  |   |
- Metabolic cost reduction when active actuators are added to loaded gait model:
- optimalOptimal: 10.35% reduction
- Saturated: 1.84% reduction
- New CMC: 2.68% reduction
- Metabolic cost reduction when active actuators are added to unloaded gait modemodel:
- optimalOptimal: 10.62% reduction
- Saturated: 3.46% reduction
- New CMC: 3.82% reduction
- The result from the new CMC procedure reduces metabolic cost more efficiently.
- However, the reduction is not significant, and it is much lower than the optimal case.
- The interesting thing is that the realistic actuation input force works better in the unloaded walking case than the loaded walking case. It makes sense because we requires require lower force to assist unloaded walking than to assist loaded walking.
Biarticular actuator
Now that we know both the ankle actuator and the hip actuator works well to can reduce metabolic cost during loaded walking, the a natural progress progression is to create biarticular actuator test actuators which can affect both ankle plantar flexion plantarflexion and hip extension. In order to To reduce the number of actuatoractuators, I created biarticular actuator with 1 DOF, and see how much it reduces metabolic cost, and what it’s optimal input force is.
Modeling
Simulation result
added single-degree-of-freedom biarticular actuators affecting ankle plantarflexion and hip extension to legs on both sides, and investigate the metabolic cost. The main idea in creating a biarticular actuator is to let the path actuator go through the axis of ankle joint rotation. I chose the attachment points of the ankle and hip actuators as the via points and end points of the biarticular actuator line, and also set the origin of the ankle joint rotation as one of the via points. By doing so, I created a biarticular actuator which combines the effects of the ankle and hip actuators.
Simulation result
I ran CMC on the loaded gait model with the biarticular actuator. I set the maximum force of the biarticular actuator to be 10,000N in order to see the optimal input force and the best possible metabolic cost reduction.
| Optimal input | Metabolic cost reduction |
|---|---|
  |   |
- Metabolic cost reduction when biarticular actuators are added to loaded gait is 3.12% from baseline. It is much lower than reduction rate of ankle actuator the reduction observed using either the ankle or hip actuator.
- Control input is noisycomplex, which makes it hard to realize.
- Biarticular The biarticular actuator is not as effective as uni-articular the uniarticular actuators in terms of metabolic cost reduction.
Conclusion
...
Conclusions
- Three types of active actuators are evaluated in terms of metabolic cost reduction and controllability:
- If we can apply a sufficient amount of force, it is better to apply force to the ankle joint.
- If not, the hip actuator is a good alternative, even though it is hard difficult to control
...
- .
- The biarticular actuator doesn’t assist loaded walking very well and the force input is not consistent.
- Active actuators offer greater assist for loaded walking than unloaded walking Optimal input of when we can apply a sufficient amount of force.
- The optimal input for the ankle actuator is consistent with gait cycle and muscle forces force data, while that of hip actuator is notin contrast to the optimal input for the hip and biarticular actuators.
- The optimal input force for the ankle actuator when it’s its maximum force is bounded is similar to the general optimal input force when it is saturated at the maximum forceBiarticular actuator doesn’t assist loaded walking very well and the force input is not consistent.
Limitations
- The experimental data was obtained from a subject without an exosuit. Exosuit The exosuit may change the kinematics of a subject as well as GRFthe ground-reaction forces.
- The simulation methodology to use CMC as an optimization tool works, but more improvement is needed.
- The CMC process doesn’t minimize metabolic cost. Instead, it minimizes the 2-norm of activation.
- The experimental data is involved only one gait cycle.
- More realistic actuator simulation is simulations are needed . (Ee.g. Combination , a combination of passive & and active actuatoractuators).
Source
...
Code
You can find the model simulation models that I created for the project in SimTK website. Please visit http://www.simtk.org/~~~
...
on my Simtk project page.
| Panel | ||||||||
|---|---|---|---|---|---|---|---|---|
| ||||||||
Home: BIOE-ME 485 Spring 2013 |