This paper introduces a virtual wheel-terrain interaction model developed and validated for the UAE Rashid rover to enhance simulation accuracy for space rovers. The model incorporates wheel grouser properties, slippage, soil properties, and interaction mechanics, validated via lunar soil simulation. Experiments tested a Grouser-Rashid rover wheel at slip ratios of 0, 0.25, 0.50, and 0.75. Why it matters: This simulation method advances rover design and control, crucial for the UAE's space exploration program and lunar mission success.
This paper introduces a Bayesian optimization method for estimating tire parameters and their uncertainty, addressing a gap in existing literature. The methodology uses Stochastic Variational Inference to estimate parameters and uncertainties, and it is validated against a Nelder-Mead algorithm. The approach is applied to real-world data from the Abu Dhabi Autonomous Racing League, revealing uncertainties in identifying curvature and shape parameters due to insufficient excitation. Why it matters: The research provides a practical tool for assessing tire model parameters in real-world conditions, with implications for autonomous racing and vehicle dynamics modeling in the GCC region.
Team TII EuroRacing (TII-ER) developed a full autonomous software stack for oval racing, enabling speeds above 75 m/s (270 km/h). The software includes modules for perception, planning, control, vehicle dynamics modeling, simulation, telemetry, and safety. The team achieved second and third place in the first two Indy Autonomous Challenge events using this stack.