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🐕‍🦺 Leash Training: From Pulling to Perfect Walks (2D)

2D top-down leash-training lab: a wandering distraction pulls a dog outward against a hard leash-length constraint while you compare no-correction, stop-and-go and treat-reinforcement training methods on a live walk-quality score.

Animals & Their World2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

This 2D companion drives the same leash-tension tug-of-war as the 3D version through a plain top-down canvas view: a side panel exposes distraction drive, leash length and walking speed, a hard leash-length constraint yanks the dog back the instant it runs out of slack, and switching between no-correction, stop-and-go and treat-reinforcement training methods visibly changes whether the walk-quality score climbs toward loose-leash walking or falls as pulling gets reinforced.

⚙ Under the hood

2D top-down leash-training lab with a wandering distraction, a hard leash-length constraint, and three selectable training methods driving a live walk-quality score.

dog trainingleash walkingbehavior simulationreinforcementpet behavior

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install

Why does the leash go from green to red?

Green means the dog-to-handler distance is under the leash length (loose); red means the dog has reached the end of its slack (taut) and a pull-back force is being applied.

Which training method reduces pulling fastest?

Stop-and-Go and Loose-Leash + Treats both reward loose-leash position and raise the walk-quality score over time; No Correction keeps rewarding pulling with forward motion, so the dog's distraction drive creeps upward instead.