Keywords
nonlinear control
robot localization
mobile robots
path tracking
visual servocontrol
How to Cite
Abstract
Research on mobile robots continues to expand due to their versatility in industrial, agricultural, and rescue applications. This article reviews control strategies for wheeled non‑holonomic mobile robots using external overhead cameras in an eye‑to‑hand configuration. Unlike gps or onboard sensors, this approach reduces dependence on external signals and minimizes instrumentation costs. The review highlights that most proposals employ nonlinear visual controllers without calibration, compensating for intrinsic and extrinsic camera parameters through adaptive laws. These methods allow robust localization, position regulation, and trajectory tracking, even under dynamic disturbances. Some works incorporate calibration, via geometric markers or dual‑camera setups, achieving higher precision but at greater complexity. The analysis shows that eye‑to‑hand systems can be particularly effective in structured indoor environments, where a fixed camera can reliably track robot movements. Future perspectives emphasize integrating computer vision with artificial intelligence as a way to improve autonomy, reliability, as well as adaptability in more complex scenarios. Overall, the tendency aims toward low‑cost, flexible, and resilient visual control systems able to expand mobile robot applicability in real‑world tasks.
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