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RISS 인기검색어
- 검색키워드
- 주제어 : 4D configuration space (검색결과 2 건)
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김수현 성균관대학교 일반대학원 2017 국내박사
Smooth path generation in the car-like vehicles is one of most important requisite to facilitate autonomous navigation. This thesis proposes a smooth path generation method for nonholonomic vehicles which has inherently continuity of curvature and the path gets flexibility for various boundary conditions. The continuous curvature path is constructed by composing multiple clothoids including line or arc segment, and each clothoid is positioned by parameter regulation, from those properties the path is named as parametric Continuous Curvature Path or pCCP and provides curvature diagram which facilitates a smooth steering control in the path following. Local pCCP problem is defined by initial and final tuple configurations, and the problem is expanded to be as general as possible by including several cases. The local pCCP generation for steady target pose is specifically described, where the problem is divided as three problems and each problem is also decomposed into a few case(s). To give flexibility in the proposed pCCP, dynamic target is considered to make d-pCCP. A simple but efficient framework to analyze the future status of obstacle avoidance is applied in 4D (3D and time axis) configuration and two avoidance maneuvers as front and rear avoidance are described for exemplar demonstrations. Under the similar methodology in performance criteria of pCCP generation, the h-CCP is derived from the experimental patterns of human driver samples. From a few sub-experiments, human driving pattern for obstacle avoidance, lane change and cornering motion are extracted and those pattern were included to make a h-CCP (which is similar to pCCP but different in the optimization criteria in the generating methodology) to enhance human comfort. The contribution points for the thesis are found in its general algorithmic method for covering various boundary configurations in generating continuous curvature path, especially dealing with clothoid segments. Several algorithms are also described in the decomposed problems to make local pCCP and each obtained path solution is expanded to be utilized to generate globally smooth path. Flexibility in the pCCP could be also found as its contribution by analyzing velocity planning for obstacle avoidance in 4D space and replanning for dynamic target. The methodology to compromise the mathematically or computationally given performance criteria with the human driving database is a good tackling point for enhancing the autonomous navigated vehicles maneuvers.
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