def step(self, tau=None):
if tau is None:
tau = np.zeros(self.nj)
if not isinstance(tau, np.ndarray):
tau = tau.detach().cpu().numpy()
zero_gains = np.zeros(self.nj)
p.setJointMotorControlArray(self.robot_id,
self.bullet_joint_ids,
p.TORQUE_CONTROL,
forces=tau,
positionGains=zero_gains,
velocityGains=zero_gains)
p.stepSimulation()
q, v = self.get_state()
q = self.wrap(q)
obs = np.concatenate((q, v))
if self.cost is None:
obs_reward = 0
act_reward = 0
else:
cost = self.cost(torch.Tensor(obs), torch.Tensor(tau))
obs_reward = -cost.obs.detach().cpu().numpy()
act_reward = -cost.act.detach().cpu().numpy()
reward = obs_reward + act_reward
info = DotMap()
info.obs_reward = obs_reward
info.act_reward = act_reward
info.reward = reward
done = False
return obs, reward, done, info
