🌊 Adds control flow, kinematic and motion controller docs

This commit is contained in:
Rune Harlyk
2024-11-19 17:20:40 +01:00
parent ba9d8e1bec
commit 852ff91b7d
2 changed files with 86 additions and 0 deletions
Binary file not shown.

After

Width:  |  Height:  |  Size: 70 KiB

+86
View File
@@ -39,8 +39,55 @@ By focusing on practicality and simplicity in both hardware and software, it off
- **Self-Hosted**: Complete autonomy, from code to execution.
<!-- * Servo calibration tool -->
## 📐 Robot specifications
### 🌊 Robot control flow
The robots is implemented using a sense, plan, act control flow.
![control flow](images/flowchart.png)
## 🦾 Kinematics
To enable complex movements, it's beneficial to be able to describe the robot state using a world reference frame, instead of using raw joint angles.
The robot's body pose in the world reference frame is represented as
$$T_{body}=\left[x_b,y_b,z_b,\phi, \theta,\psi\right]$$
Where
- $x_b, y_b, z_b$ are cartesian coordinates of the robot's body center.
- $\phi, \theta,\psi$ are the roll, pitch and yaw angles, describing the body orientation.
The feet positions in the world reference frame are:
$$P_{feet}=\\{(x_{f_i},y_{f_i},z_{f_i})|i=1,2,3,4\\}$$
where $x_{f_i}, y_{f_i}, z_{f_i}$ are cartesian coordinates for each foot $i$.
Solving the inverse kinematics yields target angles for the actuators.
<!-- Write about the calculation, rotation matrix and trig -->
<!-- L1, L2, L3, L4, L, W -->
<!-- $$
R_{body} =
\begin{bmatrix}
\cos\psi\cos\theta & \cos\psi\sin\theta\sin\phi - \sin\psi\cos\phi & \cos\psi\sin\theta\cos\phi + \sin\psi\sin\phi \\
\sin\psi\cos\theta & \sin\psi\sin\theta\sin\phi + \cos\psi\cos\phi & \sin\psi\sin\theta\cos\phi - \cos\psi\sin\phi \\
-\sin\theta & \cos\theta\sin\phi & \cos\theta\cos\phi
\end{bmatrix}
$$ -->
### 🎮 Controller
The controller is a svelte app, which get embedded in the firmware of the robot.
Which mean that new releases and OTA updates includes the latest controller.
The controller includes full control over robot settings like network and calibration, and a visualization.
<img src="images/controller.gif" alt="controller" width="500">
### 🛠️ Documentation
@@ -64,6 +111,45 @@ You can find a description for the current esp32 firmware and controller [here](
The kinematic for the robot is from this [kinematics paper](https://www.researchgate.net/publication/320307716_Inverse_Kinematic_Analysis_Of_A_Quadruped_Robot). A C++ and TypeScript library was written to enable onboard calculation and fast development iteration using the robot mirroring.
-->
## 🏁 Motion state controller
The motion controller is a finite state machine with state allowing for static and dynamic posing, 8-phase crawl and bezier based trot gait, and choreographed animation.
### Controller Input Mapping
The controller input is interpret different between the modes. For the walking it it looks like this:
| Controller Input | Mapped to Gait Step | Range |
| ---------------- | ------------------- | ------- |
| Left x joystick | Step x | -1 to 1 |
| Left y joystick | Step z | -1 to 1 |
| Right x joystick | Step angle | -1 to 1 |
| Right y joystick | Body pitch angle | -1 to 1 |
| Height slider | Body height | 0 to 1 |
| Speed slider | Step velocity | 0 to 1 |
| S1 slider | Step height | 0 to 1 |
| Stop button | E stop command | 0 or 1 |
<!-- ### Static and dynamic posing -->
### 8-phase crawl gait
The 8-phase crawl gait works by lifting one leg at a time while shifting its body weight away from the leg.
As the name implies, the gait consist of 8 discrete phases, which represents which feet should be contact the ground or be in swing.
At each time step the phase time $t\in [0,1]$ is updated. When $t\geq 1$ the phase index is updated and phase time is reset.
Is derived from [mike4192 spotMicro](https://github.com/mike4192/spotMicro)
### Trot gait (12 point bezier curve)
The trot gait implements a phase time $t\in[0,1]$, but instead of using contact phases we define a swing/stance ratio of phase time offset for each leg.
The stance controller implements a sin curve to control the depth of steps.
The swing controller implements a bezier curve using 12 control points centered around the robot leg.
Rotation is calulated using the same curve
## 🔮 Getting started
1. Clone and open the new project