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 il_min_abs_jerkiness(): name = f'samples/{inspect.currentframe().f_code.co_name}.pkl' sampler.sample(N=10000, alpha=0.1, prior_file='samples/il_prior.pkl', N_sigma=1000, behavior_func=behavior.min_jerkiness, env=environment.RBF2dGymEnv(use_lidar=True), env_kernel=kernel.RBF2dEnvKernelNormal(), controller=controller.ILController(), controller_kernel=kernel.TransitionKernel(), target_type='match', target_behavior=0, save=name)
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 il_max_avg_obstacle_clearance(): name = f'samples/{inspect.currentframe().f_code.co_name}.pkl' sampler.sample(N=10000, alpha=0.1, prior_file='samples/il_prior.pkl', N_sigma=1000, behavior_func=behavior.obstacle_clearance, env=environment.RBF2dGymEnv(use_lidar=True), env_kernel=kernel.RBF2dEnvKernelNormal(), controller=controller.ILController(), controller_kernel=kernel.TransitionKernel(), target_type='maximal', save=name)
def il_min_legibility(prior_file='samples/il_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.neg_behavior(behavior.legibility), env=environment.RBF2dGymEnv(use_lidar=True), env_kernel=kernel.RBF2dEnvKernelNormal(), controller=controller.ILController(), controller_kernel=kernel.TransitionKernel(), target_type='maximal', 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)
def ds_min_avg_obstacle_clearance(): name = f'samples/{inspect.currentframe().f_code.co_name}.pkl' sampler.sample(N=10000, alpha=0.1, prior_file='samples/ds_prior.pkl', N_sigma=1000, behavior_func=behavior.obstacle_clearance, env=environment.RBF2dGymEnv(time_limit=500, oob_termination=False, use_lidar=False), env_kernel=kernel.RBF2dEnvKernelNormal(), controller=controller.DSController(), controller_kernel=kernel.TransitionKernel(), target_type='match', target_behavior=0, save=name)