simple_humanoid_env.py 文件源码

def step(self, action):
        self.forward_dynamics(action)
        next_obs = self.get_current_obs()

        alive_bonus = self.alive_bonus
        data = self.model.data

        comvel = self.get_body_comvel("torso")

        lin_vel_reward = comvel[0]
        lb, ub = self.action_bounds
        scaling = (ub - lb) * 0.5
        ctrl_cost = .5 * self.ctrl_cost_coeff * np.sum(
            np.square(action / scaling))
        impact_cost = .5 * self.impact_cost_coeff * np.sum(
            np.square(np.clip(data.cfrc_ext, -1, 1)))
        vel_deviation_cost = 0.5 * self.vel_deviation_cost_coeff * np.sum(
            np.square(comvel[1:]))
        reward = lin_vel_reward + alive_bonus - ctrl_cost - \
            impact_cost - vel_deviation_cost
        done = data.qpos[2] < 0.8 or data.qpos[2] > 2.0

        return Step(next_obs, reward, done)