def rrt_min_legibility():
name = f'samples/{inspect.currentframe().f_code.co_name}.pkl'
sampler.sample(N=10000, alpha=0.1, prior_file='samples/rrt_prior.pkl', N_sigma=1000,
behavior_func=behavior.neg_behavior(behavior.legibility),
env=environment.RBF2dGymEnv(use_lidar=False), env_kernel=kernel.RBF2dEnvKernelNormal(),
controller=controller.RRTController(), controller_kernel=kernel.RRTKernelNormal([-1, -1], [1, 1]),
target_type='maximal', save=name)
def rrt_min_abs_jerkiness():
name = f'samples/{inspect.currentframe().f_code.co_name}.pkl'
sampler.sample(N=10000, alpha=0.1, prior_file='samples/rrt_prior.pkl', N_sigma=1000,
env=environment.RBF2dGymEnv(use_lidar=False), controller=controller.RRTController(),
behavior_func=behavior.min_jerkiness, env_kernel=kernel.RBF2dEnvKernelNormal(),
controller_kernel=kernel.RRTKernelNormal([-1, -1], [1, 1]),
target_type='match', target_behavior=0, save=name)
def rrt_max_avg_obstacle_clearance(prior_file='samples/rrt_prior.pkl'):
name = f'samples/{inspect.currentframe().f_code.co_name}.pkl'
sampler.sample(N=10000, alpha=0.1, prior_file=prior_file, N_sigma=1000,
behavior_func=behavior.obstacle_clearance,
env=environment.RBF2dGymEnv(use_lidar=False), env_kernel=kernel.RBF2dEnvKernelNormal(),
controller=controller.RRTController(), controller_kernel=kernel.RRTKernelNormal([-1, -1], [1, 1]),
target_type='maximal', save=name)