Path Optimization for Ground Vehicles in Off-Road Terrain
被引:7
作者:
Overbye, Timothy
论文数: 0引用数: 0
h-index: 0
机构:
Texas A&M Univ, Dept Mech Engn, College Stn, TX 77840 USATexas A&M Univ, Dept Mech Engn, College Stn, TX 77840 USA
Overbye, Timothy
[1
]
Saripalli, Srikanth
论文数: 0引用数: 0
h-index: 0
机构:
Texas A&M Univ, Dept Mech Engn, College Stn, TX 77840 USATexas A&M Univ, Dept Mech Engn, College Stn, TX 77840 USA
Saripalli, Srikanth
[1
]
机构:
[1] Texas A&M Univ, Dept Mech Engn, College Stn, TX 77840 USA
来源:
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
|
2021年
关键词:
CURVATURE;
CURVES;
D O I:
10.1109/ICRA48506.2021.9561291
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
We present a method for path optimization for ground vehicles in off-road environments at high speeds. This path optimization considers the kinematic constraints of the vehicle. By thinking in the actuator space we can represent such constraints as limits in the space rather than derived properties of the path. In this paper we present an actuator space approach to path optimization for off-road ground vehicles. This is done by representing the path as a list of steering angles over the path length. This transforms the set of kinematic constraints into constraints on the steering angle. We then put this path into a gradient descent solver. This produces paths that are kinematically feasible and optimized in accordance with our cost function. Finally, we tested the system both in simulation and on an off-road vehicle at speeds of 5 m/s.