steering-behaviors skill

Overview

This skill implements classic steering behaviors for agents to move naturally in virtual environments. It provides primitives like seek, flee, arrive, flocking (separation, alignment, cohesion), obstacle avoidance, and path following. The focus is on composable, real-time forces that produce emergent group movement and robust collision handling.

How this skill works

Each behavior computes a steering force vector based on agent state, targets, and nearby entities. Forces are combined, weighted, and constrained by physical limits (max speed, max force) to produce smooth motion. Spatial queries and simple obstacle geometry allow efficient avoidance and flocking at scale.

When to use it

• Creating natural movement for NPCs, drones, or simulated animals
• Coordinating multi-agent formations and group behaviors
• Implementing collision-free navigation in open environments
• Following predefined paths while adapting to dynamic obstacles

Best practices

• Tune individual behavior weights and radii to balance responsiveness and stability
• Clamp combined forces to a max force and apply smoothing to prevent jitter
• Use spatial partitioning (grid, quadtree) for large numbers of agents to keep queries cheap
• Blend path following with avoidance by prioritizing immediate collision responses
• Test behaviors in varied densities and obstacle layouts to find robust defaults

Example use cases

• Swarm robotics simulation where dozens of units maintain formation and avoid collisions
• Game NPCs that travel together, split, and reunite while navigating complex maps
• Virtual crowd systems for architectural walkthroughs or event simulations
• Autonomous vehicle prototypes that follow lanes and dodge dynamic obstacles
• Research experiments on emergent group dynamics and behavior tuning

FAQ