Skip to main content

Simulation environment of task with autonomous mobile robot using Navigation Stack

Project description

navstack-gym

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.

Implemented Task

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.

Installation

pip install navstack-gym

Usage

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'))

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

navstack-gym-0.1.16.tar.gz (7.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

navstack_gym-0.1.16-py3-none-any.whl (8.4 kB view details)

Uploaded Python 3

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page