Reinforcement Learning Based Optimal Control: A Survey of Adaptive Dynamic Programming for Manipulators and Wheeled Mobile Robots

A Reinforcement Learning-Based Robust Path Tracking Controller for Nonlinear Mobile Robot Dynamics under Uncertainty

Adaptive dynamic programming for coordinated control of a dual-arm reconfigurable manipulator with unknown object constraints

Concentrating on various types of grasped objects, this work presents a distributed coordinated control scheme for a dual-arm reconfigurable manipulator (DRM) via adaptive dynamic programming (ADP). Kinematic and force analyses are performed to formulate the dynamics of a single-arm manipulator and the object using joi...

Reinforcement Learning for Real-Time Control Using Quanser Platforms: A Structured Narrative Review

A comprehensive review of published RL-based control studies using the Quanser Aero, Aero 2, 3-DOF Helicopter, and Autonomous Vehicles Research Studio (AVRS) platforms identifies standardised evaluation procedures, reproducible reporting, safety-aware RL, interoperable software interfaces, and higher-fidelity digital t...

Adaptive-optimal control of vehicle lateral dynamics via integral-reinforcement-learning actor–critic policy iteration

Simulation results show that the IRL actor–critic controller matches or improves upon the fixed-gain baseline after a plant change while, unlike the certainty-equivalence scheme, requiring no continuous probing/dither signal for identifiability—avoiding the associated persistent tracking-error penalty.

A Review of Robot Adaptive Control Driven by Deep Reinforcement Learning

In complex settings like smart manufacturing and human-robot teamwork, robots face internal disturbances and external uncertainties. Traditional control methods depend on accurate models and manual parameter tuning, leading to complex adjustment, weak dist urbance rejection, and poor generalization. Deep reinforcement...

Reinforcement Learning for Quadrupedal Robot Control: Taxonomy, Sim-to-Real, Robustness, and Emerging Trends

. Quadrupedal robots exhibit strong mobility in complex environments where wheeled platforms often perform poorly, but their control remains difficult. In recent years, reinforcement learning (RL) has received growing attention in quadrupedal locomotion, as it supports direct policy optimization without relying entirel...