Reactive Control

Reactive control focuses on designing systems that respond directly to immediate sensory input, enabling real-time adaptation to dynamic environments without relying on pre-planned trajectories. Current research emphasizes the application of reactive control in diverse areas, including robotics (e.g., mobile manipulation, human-robot collaboration), and energy-efficient building management (e.g., HVAC systems), often leveraging deep reinforcement learning algorithms like SAC and TD3, or model predictive control techniques. This approach is significant for improving the robustness, efficiency, and safety of autonomous systems in unpredictable conditions, leading to advancements in areas such as assistive robotics, autonomous navigation, and resource optimization.