Speaker
Description
Heavy forestry machinery like harvesters or forwarders may damage machine operating trails during their operation by causing rut formation. This damage is mostly due to a combination of the loaded weight of these machines and soil condition, which can also result in increased wheel slip. Therefore, having a method to calculate slip in real time will result in a better understanding of caused soil damage.
The purpose of this presentation is to estimate wheel slip of forest machines in real time on machine operating trails by proposing a combined radar and wheel-encoder approach. The proposed solution is independent of machine make and model since it relies completely on external sensors making it modular for integration into existing systems. The core of this approach relies on using one wheel encoder on each side of each bogie axle to measure wheel rotation speed. A radar is then used to measure the real velocity of the ego vehicle, which is independent from wheel slip. As of current knowledge, there are no control systems on forest machines that use RADAR to calculate ego velocity. By evaluating both of these values, wheel slip can be numerically computed in real time. The evaluation of this method is currently being assessed in an ongoing project.
By providing real time slip calculation, advanced systems (like operator assistance or autonomous driving modes) can utilize it and indicate if operation of the machine can continue or if it should be halted, as predicted rut depth exceeds regulatory limits.
| Keywords | Driving-Assistance; Sensors; Slippage; Terramechanics |
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