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Version vom 17. Dezember 2018, 18:07 Uhr

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Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)

Holger Banzhaf was awarded with the Best Paper Award for his paper named From G2 to G3 Continuity: Continuous Curvature Rate Steering Functions for Sampling-Based Nonholonomic Motion Planning at IV 2018.

Abstract
Motion planning for car-like robots is one of the major challenges in automated driving. It requires to solve a two-point boundary value problem (BVP) in real time while taking into account the nonholonomic constraints of the vehicle and the obstacles in the non-convex environment. This paper introduces Hybrid Curvature Rate (HCR) and Continuous Curvature Rate (CCR) Steer: Two novel steering functions for car-like robots that compute a curvature rate continuous solution of the two-point BVP. Hard constraints on the maximum curvature, maximum curvature rate, and maximum curvature acceleration are satisfied resulting in directly driveable G3 continuous paths. The presented steering functions are benchmarked in terms of computation time and path length against its G1 and G2 continuous counterparts, namely Dubins, Reeds-Shepp, Hybrid Curvature, and Continuous Curvature Steer. It is shown that curvature rate continuity can be achieved with only small computational overhead. The generic motion planner Bidirectional RRT* is finally used to present the effectiveness of HCR and CCR Steer in three challenging automated driving scenarios.

Aus der Forschungsgruppe Angewandte Technisch-Kognitive Systeme

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 |Titel EN=Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)
 |Beschreibung DE='''Holger Banzhaf was awarded with the Best Paper Award for his paper named ''From G2 to G3 Continuity: Continuous Curvature Rate Steering Functions for Sampling-Based Nonholonomic Motion Planning'' at IV 2018.'''<br><br>'''Abstract'''<br>Motion planning for car-like robots is one of the major challenges in automated driving. It requires to solve a two-point boundary value problem (BVP) in real time while taking into account the nonholonomic constraints of the vehicle and the obstacles in the non-convex environment. This paper introduces Hybrid Curvature Rate (HCR) and Continuous Curvature Rate (CCR) Steer: Two novel steering functions for car-like robots that compute a curvature rate continuous solution of the two-point BVP. Hard constraints on the maximum curvature, maximum curvature rate, and maximum curvature acceleration are satisfied resulting in directly driveable G3 continuous paths. The presented steering functions are benchmarked in terms of computation time and path length against its G1 and G2 continuous counterparts, namely Dubins, Reeds-Shepp, Hybrid Curvature, and Continuous Curvature Steer. It is shown that curvature rate continuity can be achieved with only small computational overhead. The generic motion planner Bidirectional RRT* is finally used to present the effectiveness of HCR and CCR Steer in three challenging automated driving scenarios.
-|Beschreibung EN='''Holger Banzhaf was awarded with the Best Paper Award for his paper named ''From G2 to G3 Continuity: Continuous Curvature Rate Steering Functions for Sampling-Based Nonholonomic Motion Planning
+|Beschreibung EN='''Holger Banzhaf was awarded with the Best Paper Award for his paper named ''From G2 to G3 Continuity: Continuous Curvature Rate Steering Functions for Sampling-Based Nonholonomic Motion Planning'' at IV 2018.'''<br><br>'''Abstract'''<br>Motion planning for car-like robots is one of the major challenges in automated driving. It requires to solve a two-point boundary value problem (BVP) in real time while taking into account the nonholonomic constraints of the vehicle and the obstacles in the non-convex environment. This paper introduces Hybrid Curvature Rate (HCR) and Continuous Curvature Rate (CCR) Steer: Two novel steering functions for car-like robots that compute a curvature rate continuous solution of the two-point BVP. Hard constraints on the maximum curvature, maximum curvature rate, and maximum curvature acceleration are satisfied resulting in directly driveable G3 continuous paths. The presented steering functions are benchmarked in terms of computation time and path length against its G1 and G2 continuous counterparts, namely Dubins, Reeds-Shepp, Hybrid Curvature, and Continuous Curvature Steer. It is shown that curvature rate continuity can be achieved with only small computational overhead. The generic motion planner Bidirectional RRT* is finally used to present the effectiveness of HCR and CCR Steer in three challenging automated driving scenarios.
-'' at IV 2018.'''<br><br>'''Abstract'''<br>Motion planning for car-like robots is one of the major challenges in automated driving. It requires to solve a two-point boundary value problem (BVP) in real time while taking into account the nonholonomic constraints of the vehicle and the obstacles in the non-convex environment. This paper introduces Hybrid Curvature Rate (HCR) and Continuous Curvature Rate (CCR) Steer: Two novel steering functions for car-like robots that compute a curvature rate continuous solution of the two-point BVP. Hard constraints on the maximum curvature, maximum curvature rate, and maximum curvature acceleration are satisfied resulting in directly driveable G3 continuous paths. The presented steering functions are benchmarked in terms of computation time and path length against its G1 and G2 continuous counterparts, namely Dubins, Reeds-Shepp, Hybrid Curvature, and Continuous Curvature Steer. It is shown that curvature rate continuity can be achieved with only small computational overhead. The generic motion planner Bidirectional RRT* is finally used to present the effectiveness of HCR and CCR Steer in three challenging automated driving scenarios.
 |Datum=2018/06/28
 |Forschungsgruppe=Angewandte Technisch-Kognitive Systeme
 }}