def init_agent_state(self, agent_id):
# initialize the agent at a random start state
agent = self._sim.initialize_agent(agent_id)
start_state = agent.get_state()
if (start_state.position != self.init_position).any():
start_state.position = self.init_position
start_state.rotation = q.from_float_array(self.init_rotation)
start_state.sensor_states = dict() ## Initialize sensor
agent.set_state(start_state)
return start_state
def init_agent_state(self, agent_id):
# initialize the agent at a random start state
agent = self._sim.initialize_agent(agent_id)
start_state = agent.get_state()
# force starting position on first floor (try 100 samples)
num_start_tries = 0
while start_state.position[1] > 0.5 and num_start_tries < 100:
start_state.position = self._sim.pathfinder.get_random_navigable_point()
num_start_tries += 1
agent.set_state(start_state)
if not self._sim_settings["silent"]:
print(
"start_state.position\t",
start_state.position,
"start_state.rotation\t",
start_state.rotation,
)
return start_state