ValueError: high - low < 0 for env.reset()

[LeoHink]

When I run env.reset() now and then, I get this error ValueError: high - low < 0; it is hard to reproduce this error. It occurs somewhat randomly. I have no idea why this is occurring. In particular, it seems to occur when calling self.init_robot_pose when calling env.reset()`. This also occurs when setting a random seed. I'm testing with the scratch-itch environment. Any help would be much appreciated.

Edit: This error does not occur in Feeding environments have yet to test other so it might be isolated to scratch itch.

Full error:

ValueError                                Traceback (most recent call last)
[/var/folders/_l/435lwsyd56n753cy_66n91xh0000gn/T/ipykernel_9937/1077114707.py](https://file+.vscode-resource.vscode-cdn.net/var/folders/_l/435lwsyd56n753cy_66n91xh0000gn/T/ipykernel_9937/1077114707.py) in <module>
     21 
     22         # TRY NOT TO MODIFY: execute the game and log data.
---> 23         next_obs, reward, terminations, infos = envs.step(action.cpu().numpy())
     24         # print(terminations)
     25         # print(f"next_obs: {next_obs} \n dtype: {next_obs.dtype}")

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/vector/vector_env.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/vector/vector_env.py) in step(self, actions)
    110 
    111         self.step_async(actions)
--> 112         return self.step_wait()
    113 
    114     def call_async(self, name, *args, **kwargs):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/vector/sync_vector_env.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/vector/sync_vector_env.py) in step_wait(self)
    139             if self._dones[i]:
    140                 info["terminal_observation"] = observation
--> 141                 observation = env.reset()
    142             observations.append(observation)
    143             infos.append(info)

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py) in reset(self, **kwargs)
    322 class RewardWrapper(Wrapper):
    323     def reset(self, **kwargs):
--> 324         return self.env.reset(**kwargs)
    325 
    326     def step(self, action):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py) in reset(self, **kwargs)
    281 
    282     def reset(self, **kwargs) -> Union[ObsType, tuple[ObsType, dict]]:
--> 283         return self.env.reset(**kwargs)
    284 
    285     def render(self, mode="human", **kwargs):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py) in reset(self, **kwargs)
    309             return self.observation(obs), info
    310         else:
--> 311             return self.observation(self.env.reset(**kwargs))
    312 
    313     def step(self, action):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/normalize.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/normalize.py) in reset(self, **kwargs)
     69             obs, info = self.env.reset(**kwargs)
     70         else:
---> 71             obs = self.env.reset(**kwargs)
     72         if self.is_vector_env:
     73             obs = self.normalize(obs)

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py) in reset(self, **kwargs)
    335 class ActionWrapper(Wrapper):
    336     def reset(self, **kwargs):
--> 337         return self.env.reset(**kwargs)
    338 
    339     def step(self, action):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/record_episode_statistics.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/record_episode_statistics.py) in reset(self, **kwargs)
     20 
     21     def reset(self, **kwargs):
---> 22         observations = super().reset(**kwargs)
     23         self.episode_returns = np.zeros(self.num_envs, dtype=np.float32)
     24         self.episode_lengths = np.zeros(self.num_envs, dtype=np.int32)

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py) in reset(self, **kwargs)
    281 
    282     def reset(self, **kwargs) -> Union[ObsType, tuple[ObsType, dict]]:
--> 283         return self.env.reset(**kwargs)
    284 
    285     def render(self, mode="human", **kwargs):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/core.py) in reset(self, **kwargs)
    309             return self.observation(obs), info
    310         else:
--> 311             return self.observation(self.env.reset(**kwargs))
    312 
    313     def step(self, action):

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/time_limit.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/time_limit.py) in reset(self, **kwargs)
     24     def reset(self, **kwargs):
     25         self._elapsed_steps = 0
---> 26         return self.env.reset(**kwargs)

[~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/order_enforcing.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/anaconda3/envs/assistive_robotics/lib/python3.7/site-packages/gym/wrappers/order_enforcing.py) in reset(self, **kwargs)
     16     def reset(self, **kwargs):
     17         self._has_reset = True
---> 18         return self.env.reset(**kwargs)

[~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/scratch_itch.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/scratch_itch.py) in reset(self)
    116         target_ee_pos = np.array([-0.6, 0, 0.8]) + self.np_random.uniform(-0.05, 0.05, size=3)
    117         target_ee_orient = self.get_quaternion(self.robot.toc_ee_orient_rpy[self.task])
--> 118         self.init_robot_pose(target_ee_pos, target_ee_orient, [(target_ee_pos, target_ee_orient)], [(shoulder_pos, None), (elbow_pos, None), (wrist_pos, None)], arm='left', tools=[self.tool], collision_objects=[self.human, self.furniture])
    119 
    120         # Open gripper to hold the tool

[~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/env.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/env.py) in init_robot_pose(self, target_ee_pos, target_ee_orient, start_pos_orient, target_pos_orients, arm, tools, collision_objects, wheelchair_enabled, right_side, max_iterations)
    294             elif self.robot.wheelchair_mounted and wheelchair_enabled:
    295                 # Use IK to find starting joint angles for mounted robots
--> 296                 self.robot.ik_random_restarts(right=(arm == 'right'), target_pos=target_ee_pos, target_orient=target_ee_orient, max_iterations=1000, max_ik_random_restarts=1000, success_threshold=0.01, step_sim=False, check_env_collisions=False, randomize_limits=True, collision_objects=collision_objects)
    297             else:
    298                 # Use TOC with JLWKI to find an optimal base position for the robot near the person

[~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/agents/robot.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/agents/robot.py) in ik_random_restarts(self, right, target_pos, target_orient, max_iterations, max_ik_random_restarts, success_threshold, step_sim, check_env_collisions, randomize_limits, collision_objects)
     89         best_ik_distance = 0
     90         for r in range(max_ik_random_restarts):
---> 91             target_joint_angles = self.ik(self.right_end_effector if right else self.left_end_effector, target_pos, target_orient, ik_indices=self.right_arm_ik_indices if right else self.left_arm_ik_indices, max_iterations=max_iterations, half_range=self.half_range, randomize_limits=(randomize_limits and r >= 10))
     92             self.set_joint_angles(self.right_arm_joint_indices if right else self.left_arm_joint_indices, target_joint_angles)
     93             gripper_pos, gripper_orient = self.get_pos_orient(self.right_end_effector if right else self.left_end_effector)

[~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/agents/agent.py](https://file+.vscode-resource.vscode-cdn.net/Users/leohink/Documents/1_PhD/assistive_gym/~/Documents/1_PhD/assistive_gym/assistive-gym/assistive_gym/envs/agents/agent.py) in ik(self, target_joint, target_pos, target_orient, ik_indices, max_iterations, half_range, use_current_as_rest, randomize_limits)
    253         if target_orient is not None and len(target_orient) < 4:
    254             target_orient = self.get_quaternion(target_orient)
--> 255         ik_lower_limits = self.ik_lower_limits if not randomize_limits else self.np_random.uniform(0, self.ik_lower_limits)
    256         ik_upper_limits = self.ik_upper_limits if not randomize_limits else self.np_random.uniform(0, self.ik_upper_limits)
    257         ik_joint_ranges = ik_upper_limits - ik_lower_limits

_generator.pyx in numpy.random._generator.Generator.uniform()

_common.pyx in numpy.random._common.cont()

_common.pyx in numpy.random._common.cont_broadcast_2()

_common.pyx in numpy.random._common.check_array_constraint()

ValueError: high - low < 0