Comments (4)
Possible Solution
mask_index = int(car_v.angle) - 180 + self.angle
if mask_index < 0:
mask_index += 360
mask = ...
from pysimulate.
Update:
Cached 359 masks for each angle. Current implementation calculates the offset of the new angle and grabs the corresponding mask from the SensorBuilder class. An (x, y) offset is calculated (the position of the car) and the mask is moved into position.
from pysimulate.
Current implementation maintains ~55-60 fps
from pysimulate.
Using numpy arrays instead of masks (for sensors) allows for 100-120fps (when using 10 sensors)
from pysimulate.
Related Issues (20)
- Implement CI/CD pipeline for automated deployment
- Implement offset for sensor intersection circles HOT 1
- Implement number of iterations
- Add a property to Simulation that will kill the simulation if car isn't moved for a period of time.
- Implement a simulation for the genetic algorithm HOT 3
- Add tire tracks for simulation asthetics
- Implement Deep Q-Learning Algorithm
- Allow the default car to hold a 5th default state to account for no action
- Add necessary attributes to `SensorBuilder` class in `vehicle` module
- Create debugger logging option that allows for differing levels of logging to the console.
- Implement notification labels that fade out
- Create a visual for what 'keys' the driver is pressing
- Test implementation of saving model weights and loading latest models
- Add quick-keys for restarting simulation and rewarding driver
- Fine tune normalization of inputs separately
- Track all relevant attributes in the simulator/car/driver and plot using `matplotlib` or `seaborn` package
- Create headless mode for genetic algorithm simulator
- tensorflow dependency issue HOT 2
- pip install pysimulate not allowing import statement
- Create new tracks for testing
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from pysimulate.