Sudden mass changes, increased aerodynamic drag, flying in the rain, and dragging a car with an inelastic rope—these are just a few of the real-world challenges that robots face. In response, the research team led by Prof. Ke-Xin Guo from Beihang University Hangzhou Innovation Institute presented the FORESEER framework, a composite hierarchical disturbance-rejection solution for robots, published in the top-tier journal The International Journal of Robotics Research (IJRR).
The framework was systematically validated through extensive indoor and outdoor experiments across five distinct drone configurations, utilizing these four representative tasks to evaluate its performance. NOKOV Motion Capture System provided high-precision pose data and trajectory information during indoor flight missions, facilitating the validation of the framework’s effectiveness in handling diverse uncertainties.
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