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Babysitter MPC Controller Skill

Expert skill for Model Predictive Control implementation and tuning

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/robotics-simulation/skills/mpc-controller" ~/.claude/skills/a5c-ai-babysitter-mpc-controller-skill && rm -rf "$T"
manifest: library/specializations/robotics-simulation/skills/mpc-controller/SKILL.md
tags
#mpc-implementation#control-systems#optimization#casadi#acado#trajectory-planning
source content

MPC Controller Skill

Overview

Expert skill for designing, implementing, and tuning Model Predictive Controllers for robotic systems, including both linear and nonlinear MPC.

Capabilities

  • Derive kinematic and dynamic robot models
  • Formulate MPC optimization problems (QP, NLP)
  • Configure CasADi for symbolic differentiation
  • Set up ACADO code generation for real-time MPC
  • Implement constraint handling (velocity, acceleration, collision)
  • Configure cost function weights (tracking, control effort)
  • Implement warm starting for fast convergence
  • Set up NMPC for nonlinear systems
  • Configure terminal constraints and costs
  • Optimize solver parameters for real-time execution

Target Processes

  • mpc-controller-design.js
  • trajectory-optimization.js
  • dynamic-obstacle-avoidance.js
  • path-planning-algorithm.js

Dependencies

  • CasADi
  • ACADO Toolkit
  • OSQP
  • qpOASES
  • Ipopt

Usage Context

This skill is invoked when processes require advanced model-based control, trajectory tracking with constraints, or real-time optimization-based control strategies.

Output Artifacts

  • MPC formulation code
  • CasADi symbolic models
  • ACADO generated code
  • QP/NLP solver configurations
  • Cost function tuning parameters
  • Constraint specifications