kscale

# K-Scale Robotics Skill Collection **Trit**: 0 (ERGODIC - coordination/infrastructure) **Color**: #5B8DEE (Sky Blue) **URI**: skill://kscale#5B8DEE ## Overview This skill indexes the K-Scale Labs robotics ecosystem - a comprehensive open-source stack for building, training, and deploying humanoid robots. The collection follows GF(3) triadic organization with `kos-firmware` (+1) as the primary generator and `mujoco-scenes` (0) as the coordinator. ## Skill Inventory ``` ┌────────────────────────────────────────────────────────────────────┐ │ K-SCALE SKILL ECOSYSTEM │ ├────────────────────────────────────────────────────────────────────┤ │ │ │ PLUS (+1) - Generation/Construction │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ kos-firmware #79ED91 Robot firmware & gRPC services │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ │ │ ERGODIC (0) - Coordination/Infrastructure │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ mujoco-scenes #9FD875 Scene composition for MuJoCo │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ │ │ MINUS (-1) - Analysis/Verification │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ ksim-rl #3A2F9E RL training for locomotion │ │ │ │ evla-vla #DBA51D Vision-language-action model │ │ │ │ urdf2mjcf #4615B7 URDF to MJCF conversion │ │ │ │ kbot-humanoid #5B45C2 K-Bot robot specifications │ │ │ │ zeroth-bot #8CC136 3D-printed humanoid platform │ │ │ │ kscale-actuator #B9172E Robstride motor control │ │ │ │ entropy-sim2real #E85B8E Entropy-driven sim2real │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ │ └────────────────────────────────────────────────────────────────────┘ ``` ## GF(3) Balance Analysis **Current State**: UNBALANCED (trit sum = -6) | Trit | Count | Skills | |------|-------|--------| | +1 (PLUS) | 1 | kos-firmware | | 0 (ERGODIC) | 1 | mujoco-scenes | | -1 (MINUS) | 7 | ksim-rl, evla-vla, urdf2mjcf, kbot-humanoid, zeroth-bot, kscale-actuator, entropy-sim2real | ### Balanced Triads The primary balanced triad anchors the ecosystem: ``` ksim-rl (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓ ``` **Pattern**: Each MINUS skill can form a balanced triad by reusing the (kos-firmware, mujoco-scenes) pair: ``` 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 ✓ kscale-actuator (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓ entropy-sim2real (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓ ``` ### Recommendations for Balance To achieve independent balanced triads (no skill reuse), add PLUS (+1) skills: 1. **kscale-deploy** (+1): Deployment automation, OTA updates 2. **kscale-onboard** (+1): On-robot compute orchestration 3. **kscale-teleop** (+1): Teleoperation and remote control 4. **kinfer-runtime** (+1): On-device inference runtime ## Architecture ``` ┌─────────────────────┐ │ TRAINING │ │ ┌───────────────┐ │ │ │ ksim-rl │ │ │ │ (PPO, AMP) │ │ │ └───────────────┘ │ │ │ │ │ ▼ │ │ ┌───────────────┐ │ │ │ mujoco-scenes │ │ │ │ (environments)│ │ │ └───────────────┘ │ └─────────┬───────────┘ │ ┌──────────────────────┼──────────────────────┐ │ │ │ ▼ ▼ ▼ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │ MODELS │ │ PERCEPTION │ │ TRANSFER │ │ ┌─────────────┐ │ │ ┌─────────────┐ │ │ ┌─────────────┐ │ │ │ urdf2mjcf │ │ │ │ evla-vla │ │ │ │entropy-sim2r│ │ │ │ kbot-humanoi│ │ │ │ (VLA) │ │ │ │ (domain │ │ │ │ zeroth-bot │ │ │ └─────────────┘ │ │ │ random.) │ │ │ └─────────────┘ │ └─────────────────┘ │ └─────────────┘ │ └─────────────────┘ └─────────────────┘ │ │ └──────────────────────┬──────────────────────┘ │ ▼ ┌─────────────────────┐ │ DEPLOYMENT │ │ ┌───────────────┐ │ │ │ kos-firmware │ │ │ │ (+1) │ │ │ └───────────────┘ │ │ │ │ │ ▼ │ │ ┌───────────────┐ │ │ │kscale-actuator│ │ │ │ (CAN motors) │ │ │ └───────────────┘ │ └─────────────────────┘ ``` ## Usage ### Training Pipeline ```python # Full K-Scale training pipeline from ksim import PPOTask from ksim.robots.kbot import KBotConfig from mujoco_scenes import SceneBuilder, Terrain class KBotWalkingTask(PPOTask): robot = KBotConfig(model_path="kbot.mjcf") def build_scene(self): scene = SceneBuilder() scene.add_terrain(Terrain.FLAT) scene.add_random_obstacles(count=5) return scene.to_mjcf() # Entropy-driven domain randomization physics_randomizers = [ StaticFrictionRandomizer(scale=0.5), MassMultiplicationRandomizer(scale=0.2), ] # Train task = KBotWalkingTask() task.run_training(num_envs=4096) ``` ### Deployment Pipeline ```python from pykos import KosClient async def deploy_policy(): async with KosClient("kbot.local:50051") as client: # Load trained policy await client.policy.load("walking_v1.onnx") # Start control loop await client.policy.start() # Monitor while True: state = await client.actuator.get_actuators_state() print(f"Position: {state.positions}") ``` ## Key Contributors - **codekansas** (Ben Bolte): Core architecture across ksim, kos - **budzianowski**: EdgeVLA, dataset standardization - **nfreq**: KOS PolicyService, calibration - **WT-MM**: Visualization, integration - **b-vm**: Randomizers, disturbances ## Repository Links | Skill | Repository | |-------|------------| | ksim-rl | [kscalelabs/ksim](https://github.com/kscalelabs/ksim) | | kos-firmware | [kscalelabs/kos](https://github.com/kscalelabs/kos) | | evla-vla | [kscalelabs/evla](https://github.com/kscalelabs/evla) | | urdf2mjcf | [kscalelabs/urdf2mjcf](https://github.com/kscalelabs/urdf2mjcf) | | kbot-humanoid | [kscalelabs/kbot](https://github.com/kscalelabs/kbot) | | zeroth-bot | [kscalelabs/zeroth-bot](https://github.com/kscalelabs/zeroth-bot) | | mujoco-scenes | [kscalelabs/mujoco-scenes](https://github.com/kscalelabs/mujoco-scenes) | | kscale-actuator | [kscalelabs/actuator](https://github.com/kscalelabs/actuator) | ## Related Skills - `jaxlife-open-ended` (+1): Open-ended evolution for behavior discovery - `ergodicity` (0): Ergodic theory foundations - `wobble-dynamics` (0): Perturbation response analysis - `stability` (-1): Dynamical system stability analysis ## References ```bibtex @misc{kscale2024, title={K-Scale Labs Open Source Robotics Stack}, author={K-Scale Labs}, year={2024}, url={https://github.com/kscalelabs} } ``` ## SDF Interleaving This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021): ### Primary Chapter: 4. Pattern Matching **Concepts**: unification, match, segment variables, pattern ### GF(3) Balanced Triad ``` kscale (−) + SDF.Ch4 (+) + [balancer] (○) = 0 ``` **Skill Trit**: -1 (MINUS - verification) ### Secondary Chapters - Ch5: Evaluation - Ch2: Domain-Specific Languages ### Connection Pattern Pattern matching extracts structure. This skill recognizes and transforms patterns.