Package for creating different scenes in MuJoCo. Compose environments with objects, terrains, and obstacles for robot training.
Scanned 9/6/2026
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---
name: mujoco-scenes
description: Package for creating different scenes in MuJoCo. Compose environments with objects, terrains, and obstacles for robot training.
version: 1.0.0
category: robotics-simulation
author: K-Scale Labs
source: kscalelabs/mujoco-scenes
license: MIT
trit: 0
trit_label: ERGODIC
color: "#9FD875"
verified: false
featured: false
---
# MuJoCo Scenes Skill
**Trit**: 0 (ERGODIC - coordination/infrastructure)
**Color**: #9FD875 (Soft Green)
**URI**: skill://mujoco-scenes#9FD875
## Overview
Package for composing MuJoCo scenes with objects, terrains, and obstacles. Enables diverse environment generation for robot training.
## Usage
```python
from mujoco_scenes import SceneBuilder, Terrain, Object
# Build a training scene
scene = SceneBuilder()
# Add terrain
scene.add_terrain(
Terrain.FLAT,
size=(10, 10),
friction=1.0,
)
# Add obstacles
scene.add_object(
Object.BOX,
pos=(2, 0, 0.5),
size=(0.5, 0.5, 0.5),
color=(1, 0, 0, 1),
)
scene.add_object(
Object.SPHERE,
pos=(-1, 2, 0.3),
radius=0.3,
mass=0.5,
)
# Add terrain variations
scene.add_terrain(
Terrain.STAIRS,
pos=(5, 0, 0),
step_height=0.15,
step_count=5,
)
# Export to MJCF
mjcf = scene.to_mjcf()
```
## Terrain Types
```
┌─────────────────────────────────────────────────────────────┐
│ TERRAIN TYPES │
├─────────────────────────────────────────────────────────────┤
│ │
│ FLAT ═══════════════════════════ │
│ │
│ STAIRS ┌─┐ │
│ ┌─┘ └─┐ │
│ ┌─┘ └─┐ │
│ │
│ RAMP ╱╲ │
│ ╱ ╲ │
│ │
│ ROUGH ∿∿∿∿∿∿∿∿∿∿∿∿∿∿∿ │
│ (heightfield) │
│ │
│ GAPS ═══ ═══ ═══ ═══ │
│ │
└─────────────────────────────────────────────────────────────┘
```
## Domain Randomization
```python
from mujoco_scenes import DomainRandomizer
randomizer = DomainRandomizer(
terrain_roughness=(0.0, 0.1),
friction_range=(0.5, 1.5),
object_position_noise=0.2,
lighting_variation=True,
)
# Generate randomized scenes
for i in range(100):
scene = randomizer.generate()
scene.save(f"scene_{i}.mjcf")
```
## Integration with KSIM
```python
from ksim import RLTask
from mujoco_scenes import SceneBuilder
class WalkingWithObstacles(RLTask):
def build_scene(self):
scene = SceneBuilder()
scene.add_terrain(Terrain.FLAT)
scene.add_random_obstacles(count=10)
return scene.to_mjcf()
```
## GF(3) Triads
This skill acts as the **ERGODIC (0)** coordinator:
```
ksim-rl (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓
evla-vla (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓
urdf2mjcf (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓
kbot-humanoid (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓
zeroth-bot (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓
```
## Related Skills
- `ksim-rl` (-1): Uses scenes for training
- `kos-firmware` (+1): Robot firmware
- `urdf2mjcf` (-1): Model conversion
- `kbot-humanoid` (-1): K-Bot robot
## References
```bibtex
@misc{mujocoscenes2024,
title={MuJoCo Scenes: Environment Composition for Robot Training},
author={K-Scale Labs},
year={2024},
url={https://github.com/kscalelabs/mujoco-scenes}
}
```
## SDF Interleaving
This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021):
### Primary Chapter: 1. Flexibility through Abstraction
**Concepts**: combinators, compose, parallel-combine, spread-combine, arity
### GF(3) Balanced Triad
```
mujoco-scenes (○) + SDF.Ch1 (+) + [balancer] (−) = 0
```
**Skill Trit**: 0 (ERGODIC - coordination)
### Secondary Chapters
- Ch5: Evaluation
### Connection Pattern
Combinators compose operations. This skill provides composable abstractions.
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