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Simulation environment of task with autonomous mobile robot using Navigation Stack
Simulation environment of task with autonomous mobile robot using Navigation Stack.
In this environment, the agent do action of instructing relative navigation goal pose and observe a subjective occupancy map.
TreasureChestRoom
:
Agent aim to open chests in unknown rooms with keys and discover as much treasure as possible.
The rooms in which agent spawned are randomly generated such as the following structure.
Yellow cube is key, and cyan cube is treasure chest. Each object will be generated based on different set of placing rules.
pip install navstack-gym
I'll add the note later.
example:
import gym
import navstack_gym
env = gym.make('VisibleTreasureHunt-v0')
obs = env.reset(is_generate_pose=True, is_generate_room=True, obstacle_count=10)
imgs = []
imgs.append(env.render('rgb_array'))
for i in range(10):
action = env.action_space.sample()
obs, reward, done, info = env.step(action)
imgs.append(env.render('rgb_array'))
FAQs
Simulation environment of task with autonomous mobile robot using Navigation Stack
We found that navstack-gym demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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