Adds observation and action spaces to the `RLEnv` class (#206)

# Description

Adds missing observation and action spaces to the `RLEnv` class. Some
standalone scripts were using these and were erroring out since they
were not implemented.

## Type of change

- Bug fix (non-breaking change which fixes an issue)

## Checklist

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./orbit.sh --format`
- [ ] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [x] I have updated the changelog and the corresponding version in the
extension's `config/extension.toml` file

source/extensions/omni.isaac.orbit/config/extension.toml

 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.9.18"
+version = "0.9.19"
 
 # Description
 title = "ORBIT framework for Robot Learning"

source/extensions/omni.isaac.orbit/docs/CHANGELOG.rst

 Changelog
 ---------
 
+0.9.19 (2023-10-25)
+~~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added Gym observation and action spaces for the :class:`omni.isaac.orbit.envs.RLEnv` class.
+
+
 0.9.18 (2023-10-19)
 ~~~~~~~~~~~~~~~~~~
 

source/extensions/omni.isaac.orbit/omni/isaac/orbit/envs/rl_env.py

@@ -96,6 +96,15 @@ class RLEnv(BaseEnv, gym.Env):
         # print the environment information
         print("[INFO]: Completed setting up the environment...")
 
+        # setup the action and observation spaces for Gym
+        # -- observation space
+        self.observation_space = gym.spaces.Dict()
+        for group_name, group_dim in self.observation_manager.group_obs_dim.items():
+            self.observation_space[group_name] = gym.spaces.Box(low=-np.inf, high=np.inf, shape=group_dim)
+        # -- action space (unbounded since we don't impose any limits)
+        action_dim = sum(self.action_manager.action_term_dim)
+        self.action_space = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(action_dim,))
+
         # perform randomization at the start of the simulation
         self.randomization_manager.randomize(mode="startup")
         # extend UI elements

source/extensions/omni.isaac.orbit_envs/omni/isaac/orbit_envs/locomotion/locomotion_env_cfg.py

@@ -69,7 +69,9 @@ class TerrainSceneCfg(InteractiveSceneCfg):
         debug_vis=True,
         mesh_prim_paths=["/World/ground"],
     )
-    contact_forces = ContactSensorCfg(prim_path="{ENV_REGEX_NS}/Robot/.*", history_length=3, debug_vis=True)
+    contact_forces = ContactSensorCfg(
+        prim_path="{ENV_REGEX_NS}/Robot/.*", history_length=3, track_air_time=True, debug_vis=True
+    )
     # lights
     light = AssetBaseCfg(
         prim_path="/World/light",