Charging Optimization

Battery telemetry and energy data optimize charging schedules to reduce energy use and extend battery life.

Business impact

• Energy consumption — Lowers energy usage by optimizing charging schedules and reducing wasteful charging cycles
• Battery life — Extends battery longevity by preventing overcharging and managing charge cycles intelligently
• Productivity — Increases uptime of mobile robots by minimizing charging downtime and scheduling efficiently

Data requirements

• Battery telemetry data (Numeric) — Monitors battery status and health to inform charging decisions
• Energy consumption logs (Numeric) — Tracks energy usage patterns to optimize charging schedules
• Robot operational schedules (Structured) — Aligns charging times with robot usage to minimize downtime

AI methods and techniques

• Predictive AI — Forecasts optimal charging times and energy needs based on historical and real-time data
• Agentic AI — Dynamically adjusts charging policies in response to changing operational conditions

AI models and model families

GPT-4o, Llama, Custom Reinforcement Learning Models