Tag: Model Predictive Control (MPC)
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Optimality assessment of an NMPC-based GLOSA system
Introduction The assessment of solution optimality is a crucial aspect in the design of real-time control strategies for intelligent transportation systems. In the context of Green Light Optimal Speed Advisory (GLOSA), Nonlinear Model Predictive Control (NMPC) is widely adopted due to its ability to handle system constraints and nonlinear vehicle dynamics while operating in real
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Quadruped Teleoperation System
Introduction Reinforcement Learning (RL) has recently enabled agile and dynamic behaviors in legged robots. However, RL alone is not always the most suitable tool, especially for sparse, long-horizon tasks that involve complex object manipulation. Even with careful problem formulation, reward design, and curriculum learning, such tasks can remain difficult to solve using standard RL methods.