from agent.Base_Agent import Base_Agent from math_ops.Math_Ops import Math_Ops as M import math import numpy as np class Agent(Base_Agent): def __init__(self, host:str, agent_port:int, monitor_port:int, unum:int, team_name:str, enable_log, enable_draw, wait_for_server=True, is_fat_proxy=False) -> None: # define robot type robot_type = (0,1,1,1,2,3,3,3,4,4,4)[unum-1] # Initialize base agent # Args: Server IP, Agent Port, Monitor Port, Uniform No., Robot Type, Team Name, Enable Log, Enable Draw, play mode correction, Wait for Server, Hear Callback super().__init__(host, agent_port, monitor_port, unum, robot_type, team_name, enable_log, enable_draw, True, wait_for_server, None) self.enable_draw = enable_draw self.state = 0 # 0-Normal, 1-Getting up, 2-Kicking self.kick_direction = 0 self.kick_distance = 0 self.fat_proxy_cmd = "" if is_fat_proxy else None self.fat_proxy_walk = np.zeros(3) # filtered walk parameters for fat proxy self.init_pos = ([-14,0],[-9,-5],[-9,0],[-9,5],[-5,-5],[-5,0],[-5,5],[-1,-6],[-1,-2.5],[-1,2.5],[-1,6])[unum-1] # initial formation def beam(self, avoid_center_circle=False): r = self.world.robot pos = self.init_pos[:] # copy position list self.state = 0 # Avoid center circle by moving the player back if avoid_center_circle and np.linalg.norm(self.init_pos) < 2.5: pos[0] = -2.3 if np.linalg.norm(pos - r.loc_head_position[:2]) > 0.1 or self.behavior.is_ready("Get_Up"): self.scom.commit_beam(pos, M.vector_angle((-pos[0],-pos[1]))) # beam to initial position, face coordinate (0,0) else: if self.fat_proxy_cmd is None: # normal behavior self.behavior.execute("Zero_Bent_Knees_Auto_Head") else: # fat proxy behavior self.fat_proxy_cmd += "(proxy dash 0 0 0)" self.fat_proxy_walk = np.zeros(3) # reset fat proxy walk def move(self, target_2d=(0,0), orientation=None, is_orientation_absolute=True, avoid_obstacles=True, priority_unums=[], is_aggressive=False, timeout=3000): ''' Walk to target position Parameters ---------- target_2d : array_like 2D target in absolute coordinates orientation : float absolute or relative orientation of torso, in degrees set to None to go towards the target (is_orientation_absolute is ignored) is_orientation_absolute : bool True if orientation is relative to the field, False if relative to the robot's torso avoid_obstacles : bool True to avoid obstacles using path planning (maybe reduce timeout arg if this function is called multiple times per simulation cycle) priority_unums : list list of teammates to avoid (since their role is more important) is_aggressive : bool if True, safety margins are reduced for opponents timeout : float restrict path planning to a maximum duration (in microseconds) ''' r = self.world.robot if self.fat_proxy_cmd is not None: # fat proxy behavior self.fat_proxy_move(target_2d, orientation, is_orientation_absolute) # ignore obstacles return if avoid_obstacles: target_2d, _, distance_to_final_target = self.path_manager.get_path_to_target( target_2d, priority_unums=priority_unums, is_aggressive=is_aggressive, timeout=timeout) else: distance_to_final_target = np.linalg.norm(target_2d - r.loc_head_position[:2]) self.behavior.execute("Walk", target_2d, True, orientation, is_orientation_absolute, distance_to_final_target) # Args: target, is_target_abs, ori, is_ori_abs, distance def kick(self, kick_direction=None, kick_distance=None, abort=False, enable_pass_command=False): ''' Walk to ball and kick Parameters ---------- kick_direction : float kick direction, in degrees, relative to the field kick_distance : float kick distance in meters abort : bool True to abort. The method returns True upon successful abortion, which is immediate while the robot is aligning itself. However, if the abortion is requested during the kick, it is delayed until the kick is completed. avoid_pass_command : bool When False, the pass command will be used when at least one opponent is near the ball Returns ------- finished : bool Returns True if the behavior finished or was successfully aborted. ''' if self.min_opponent_ball_dist < 1.45 and enable_pass_command: self.scom.commit_pass_command() self.kick_direction = self.kick_direction if kick_direction is None else kick_direction self.kick_distance = self.kick_distance if kick_distance is None else kick_distance if self.fat_proxy_cmd is None: # normal behavior return self.behavior.execute("Basic_Kick", self.kick_direction, abort) # Basic_Kick has no kick distance control else: # fat proxy behavior return self.fat_proxy_kick() def think_and_send(self): w = self.world r = self.world.robot my_head_pos_2d = r.loc_head_position[:2] my_ori = r.imu_torso_orientation ball_2d = w.ball_abs_pos[:2] ball_vec = ball_2d - my_head_pos_2d ball_dir = M.vector_angle(ball_vec) ball_dist = np.linalg.norm(ball_vec) ball_sq_dist = ball_dist * ball_dist # for faster comparisons ball_speed = np.linalg.norm(w.get_ball_abs_vel(6)[:2]) behavior = self.behavior goal_dir = M.target_abs_angle(ball_2d,(15.05,0)) path_draw_options = self.path_manager.draw_options PM = w.play_mode PM_GROUP = w.play_mode_group #--------------------------------------- 1. Preprocessing slow_ball_pos = w.get_predicted_ball_pos(0.5) # predicted future 2D ball position when ball speed <= 0.5 m/s # list of squared distances between teammates (including self) and slow ball (sq distance is set to 1000 in some conditions) teammates_ball_sq_dist = [np.sum((p.state_abs_pos[:2] - slow_ball_pos) ** 2) # squared distance between teammate and ball if p.state_last_update != 0 and (w.time_local_ms - p.state_last_update <= 360 or p.is_self) and not p.state_fallen else 1000 # force large distance if teammate does not exist, or its state info is not recent (360 ms), or it has fallen for p in w.teammates ] # list of squared distances between opponents and slow ball (sq distance is set to 1000 in some conditions) opponents_ball_sq_dist = [np.sum((p.state_abs_pos[:2] - slow_ball_pos) ** 2) # squared distance between teammate and ball if p.state_last_update != 0 and w.time_local_ms - p.state_last_update <= 360 and not p.state_fallen else 1000 # force large distance if opponent does not exist, or its state info is not recent (360 ms), or it has fallen for p in w.opponents ] min_teammate_ball_sq_dist = min(teammates_ball_sq_dist) self.min_teammate_ball_dist = math.sqrt(min_teammate_ball_sq_dist) # distance between ball and closest teammate self.min_opponent_ball_dist = math.sqrt(min(opponents_ball_sq_dist)) # distance between ball and closest opponent active_player_unum = teammates_ball_sq_dist.index(min_teammate_ball_sq_dist) + 1 #--------------------------------------- 2. Decide action if PM == w.M_GAME_OVER: pass elif PM_GROUP == w.MG_ACTIVE_BEAM: self.beam() elif PM_GROUP == w.MG_PASSIVE_BEAM: self.beam(True) # avoid center circle elif self.state == 1 or (behavior.is_ready("Get_Up") and self.fat_proxy_cmd is None): self.state = 0 if behavior.execute("Get_Up") else 1 # return to normal state if get up behavior has finished elif PM == w.M_OUR_KICKOFF: if r.unum == 9: self.kick(120,3) # no need to change the state when PM is not Play On else: self.move(self.init_pos, orientation=ball_dir) # walk in place elif PM == w.M_THEIR_KICKOFF: self.move(self.init_pos, orientation=ball_dir) # walk in place elif active_player_unum != r.unum: # I am not the active player if r.unum == 1: # I am the goalkeeper self.move(self.init_pos, orientation=ball_dir) # walk in place else: # compute basic formation position based on ball position new_x = max(0.5,(ball_2d[0]+15)/15) * (self.init_pos[0]+15) - 15 if self.min_teammate_ball_dist < self.min_opponent_ball_dist: new_x = min(new_x + 3.5, 13) # advance if team has possession self.move((new_x,self.init_pos[1]), orientation=ball_dir, priority_unums=[active_player_unum]) else: # I am the active player path_draw_options(enable_obstacles=True, enable_path=True, use_team_drawing_channel=True) # enable path drawings for active player (ignored if self.enable_draw is False) enable_pass_command = (PM == w.M_PLAY_ON and ball_2d[0]<6) if r.unum == 1 and PM_GROUP == w.MG_THEIR_KICK: # goalkeeper during their kick self.move(self.init_pos, orientation=ball_dir) # walk in place if PM == w.M_OUR_CORNER_KICK: self.kick( -np.sign(ball_2d[1])*95, 5.5) # kick the ball into the space in front of the opponent's goal # no need to change the state when PM is not Play On elif self.min_opponent_ball_dist + 0.5 < self.min_teammate_ball_dist: # defend if opponent is considerably closer to the ball if self.state == 2: # commit to kick while aborting self.state = 0 if self.kick(abort=True) else 2 else: # move towards ball, but position myself between ball and our goal self.move(slow_ball_pos + M.normalize_vec((-16,0) - slow_ball_pos) * 0.2, is_aggressive=True) else: self.state = 0 if self.kick(goal_dir,9,False,enable_pass_command) else 2 path_draw_options(enable_obstacles=False, enable_path=False) # disable path drawings #--------------------------------------- 3. Broadcast self.radio.broadcast() #--------------------------------------- 4. Send to server if self.fat_proxy_cmd is None: # normal behavior self.scom.commit_and_send( r.get_command() ) else: # fat proxy behavior self.scom.commit_and_send( self.fat_proxy_cmd.encode() ) self.fat_proxy_cmd = "" #---------------------- annotations for debugging if self.enable_draw: d = w.draw if active_player_unum == r.unum: d.point(slow_ball_pos, 3, d.Color.pink, "status", False) # predicted future 2D ball position when ball speed <= 0.5 m/s d.point(w.ball_2d_pred_pos[-1], 5, d.Color.pink, "status", False) # last ball prediction d.annotation((*my_head_pos_2d, 0.6), "I've got it!" , d.Color.yellow, "status") else: d.clear("status") #--------------------------------------- Fat proxy auxiliary methods def fat_proxy_kick(self): w = self.world r = self.world.robot ball_2d = w.ball_abs_pos[:2] my_head_pos_2d = r.loc_head_position[:2] if np.linalg.norm(ball_2d - my_head_pos_2d) < 0.25: # fat proxy kick arguments: power [0,10]; relative horizontal angle [-180,180]; vertical angle [0,70] self.fat_proxy_cmd += f"(proxy kick 10 {M.normalize_deg( self.kick_direction - r.imu_torso_orientation ):.2f} 20)" self.fat_proxy_walk = np.zeros(3) # reset fat proxy walk return True else: self.fat_proxy_move(ball_2d-(-0.1,0), None, True) # ignore obstacles return False def fat_proxy_move(self, target_2d, orientation, is_orientation_absolute): r = self.world.robot target_dist = np.linalg.norm(target_2d - r.loc_head_position[:2]) target_dir = M.target_rel_angle(r.loc_head_position[:2], r.imu_torso_orientation, target_2d) if target_dist > 0.1 and abs(target_dir) < 8: self.fat_proxy_cmd += (f"(proxy dash {100} {0} {0})") return if target_dist < 0.1: if is_orientation_absolute: orientation = M.normalize_deg( orientation - r.imu_torso_orientation ) target_dir = np.clip(orientation, -60, 60) self.fat_proxy_cmd += (f"(proxy dash {0} {0} {target_dir:.1f})") else: self.fat_proxy_cmd += (f"(proxy dash {20} {0} {target_dir:.1f})")