An Iterative Algorithm to Symbolically Derive Generalized n-Trailer Vehicle Kinematics
Singh, Yuvraj, Jayakumar, Adithya, Rizzoni, Giorgio
–arXiv.org Artificial Intelligence
Articulated multi-axle vehicles are interesting from a control-theoretic perspective due to their peculiar kinematic offtracking characteristics, instability modes, and singularities. Holonomic and nonholonomic constraints affecting the kinematic behavior is investigated in order to develop control-oriented kinematic models representative of these peculiarities. Then, the structure of these constraints is exploited to develop an iterative algorithm to symbolically derive yaw-plane kinematic models of generalized $n$-trailer articulated vehicles with an arbitrary number of multi-axle vehicle units. A formal proof is provided for the maximum number of kinematic controls admissible to a large-scale generalized articulated vehicle system, which leads to a generalized Ackermann steering law for $n$-trailer systems. Moreover, kinematic data collected from a test vehicle is used to validate the kinematic models and, to understand the rearward yaw rate amplification behavior of the vehicle pulling multiple simulated trailers.
arXiv.org Artificial Intelligence
Mar-31-2025
- Country:
- Europe > United Kingdom
- England > Cambridgeshire > Cambridge (0.04)
- North America > United States
- Ohio (0.04)
- Europe > United Kingdom
- Genre:
- Research Report (0.64)
- Industry:
- Automobiles & Trucks (1.00)
- Transportation > Ground
- Road (1.00)
- Technology: