Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 123]
 Nplot_states
 CPath
 CState
 Nplot_statistics
 COutput
 Nsteering
 CCC00_Dubins_State_SpaceAn implementation of continuous curvature (CC) steer for a Dubins car with zero curvature at the start and goal configuration as described in: T. Fraichard and A. Scheuer, "From Reeds and Shepp's to continuous-curvature paths," IEEE Transactions on Robotics (Volume 20, Issue: 6, Dec. 2004). It evaluates all Dubins families and returns the shortest path
 CCC00_Dubins
 CCC00_Reeds_Shepp_State_SpaceAn implementation of continuous curvature (CC) steer for a Reeds-Shepp car with zero curvature at the start and goal configuration as described in: T. Fraichard and A. Scheuer, "From Reeds and Shepp's to continuous- curvature paths," IEEE Transactions on Robotics (Volume 20, Issue: 6, Dec. 2004). It evaluates all Reeds-Shepp families plus the four families TTT, TcST, TScT, TcScT, where "T" stands for a turn, "S" for a straight line and "c" for a cusp, and returns the shortest path. Topological paths are not included in this implementation
 CCC00_Reeds_Shepp
 CCC0pm_Dubins_State_SpaceAn implementation of continuous curvature (CC) steer for a Dubins car with zero curvature at the start and either positive (p) or negative (n) max. curvature at the goal configuration. It evaluates all Dubins families and returns the shortest path
 CCC0pm_Dubins
 CCC_Dubins_Path
 CCC_Dubins_State_SpaceAn implementation of continuous curvature (CC) steer for a Dubins car with arbitrary curvature at the start and goal configuration
 CCCpm0_Dubins_State_SpaceAn implementation of continuous curvature (CC) steer for a Dubins car with either positive (p) or negative (n) max. curvature at the start and zero curvature at the goal configuration. It evaluates all Dubins families and returns the shortest path
 CCCpm0_Dubins
 CCCpmpm_Dubins_State_SpaceAn implementation of continuous curvature (CC) steer for a Dubins car with either positive (p) or negative (n) max. curvature at the start and goal configuration. It evaluates all Dubins families plus the the family TTTT, where "T" stands for a turn, and returns the shortest path
 CCCpmpm_Dubins
 CConfiguration
 CControlDescription of a path segment with its corresponding control inputs
 CControllerParameters of the feedback controller
 CDubins_State_SpaceAn SE(2) state space where distance is measured by the length of Dubins curves. Note that this Dubins distance is not a proper distance metric, so nearest neighbor methods that rely on distance() being a metric (such as ompl::NearestNeighborsGNAT) will not always return the true nearest neighbors or get stuck in an infinite loop. The notation and solutions in the code are taken from:
A.M. Shkel and V. Lumelsky, “Classification of the Dubins set,” Robotics and Autonomous Systems, 34(4):179-202, 2001. DOI: 10.1016/S0921-8890(00)00127-5 The classification scheme described there is not actually used, since it only applies to “long” paths
 CDubins_PathComplete description of a Dubins path
 CEKF
 CHC00_Reeds_Shepp_State_SpaceAn implementation of hybrid curvature (HC) steer with zero curvature at the start and goal configuration as described in: H. Banzhaf et al., "Hybrid Curvature Steer: A Novel Extend Function for Sampling-Based Non- holonomic Motion Planning in Tight Environments," IEEE International Conference on Intelligent Transportation Systems (Oct. 2017). It evaluates all Reeds-Shepp families plus the four families TTT, TcST, TScT, TcScT, where "T" stands for a turn, "S" for a straight line and "c" for a cusp, and returns the shortest path
 CHC00_Reeds_Shepp
 CHC0pm_Reeds_Shepp_State_SpaceAn implementation of hybrid curvature (HC) steer with zero curvature at the start configuration and either positive (p) or negative (n) max. curvature at the goal configuration, also see: H. Banzhaf et al., "Hybrid Curvature Steer: A Novel Extend Function for Sampling-Based Non- holonomic Motion Planning in Tight Environments," IEEE International Conference on Intelligent Transportation Systems (Oct. 2017). It evaluates all Reeds-Shepp families plus the four families TTT, TcST, TScT, TcScT, where "T" stands for a turn, "S" for a straight line and "c" for a cusp, and returns the shortest path
 CHC0pm_Reeds_Shepp
 CHC_CC_Circle
 CHC_CC_Circle_Param
 CHC_CC_RS_Path
 CHC_CC_State_Space
 CHC_Reeds_Shepp_State_SpaceAn implementation of hybrid curvature (HC) steer with arbitrary curvature at the start and goal configuration
 CHCpm0_Reeds_Shepp_State_SpaceAn implementation of hybrid curvature (HC) steer with either positive (p) or negative (n) max. curvature at the start configuration and zero curvature at the goal configuration, also see: H. Banzhaf et al., "Hybrid Curvature Steer: A Novel Extend Function for Sampling-Based Non- holonomic Motion Planning in Tight Environments," IEEE International Conference on Intelligent Transportation Systems (Oct. 2017). It evaluates all Reeds-Shepp families plus the four families TTT, TcST, TScT, TcScT, where "T" stands for a turn, "S" for a straight line and "c" for a cusp, and returns the shortest path
 CHCpm0_Reeds_Shepp
 CHCpmpm_Reeds_Shepp_State_SpaceAn implementation of hybrid curvature (HC) steer with either positive (p) or negative (n) max. curvature at the start and goal configuration as described in: H. Banzhaf et al., "Hybrid Curvature Steer: A Novel Extend Function for Sampling-Based Nonholonomic Motion Planning in Tight Environments," IEEE International Conference on Intelligent Transportation Systems (Oct. 2017). It evaluates all Reeds-Shepp families plus the four families TTT, TcST, TScT, TcScT, where "T" stands for a turn, "S" for a straight line and "c" for a cusp, and returns the shortest path
 CHCpmpm_Reeds_Shepp
 CMeasurement_NoiseParameters of the measurement noise
 CMotion_NoiseParameters of the motion noise model according to the book: Probabilistic Robotics, S. Thrun and others, MIT Press, 2006, p. 127-128 and p.204-206
 CPath
 CReeds_Shepp_State_SpaceAn SE(2) state space where distance is measured by the length of Reeds-Shepp curves. The notation and solutions are taken from: J.A. Reeds and L.A. Shepp, “Optimal paths for a car that goes both forwards and backwards,” Pacific Journal of Mathematics, 145(2):367–393, 1990. This implementation explicitly computes all 48 Reeds-Shepp curves and returns the shortest valid solution. This can be improved by using the configuration space partition described in: P. Souères and J.-P. Laumond, “Shortest paths synthesis for a car-like robot,” IEEE Trans. on Automatic Control, 41(5):672–688, May 1996
 CReeds_Shepp_PathComplete description of a ReedsShepp path
 CStateDescription of a kinematic car's state
 CState_With_CovarianceDescription of a kinematic car's state with covariance
 CPathClass
 CRobotClass
 CStatistic
 CTest_HC_CC_State_Space


steering_functions
Author(s): Holger Banzhaf
autogenerated on Mon Dec 11 2023 03:27:44