fix spelling errors

Go2Py/joy.py

@@ -49,7 +49,7 @@ class xRockerBtn:
 
 class PyGameJoyManager:
     def __init__(self, user_callback=None):
-        self.dt = 0.01  # Sampling frequence of the joystick
+        self.dt = 0.01  # Sampling frequency of the joystick
         self.running = False
         self.joy_thread_handle = threading.Thread(target=self.joy_thread)
         # an optional callback that can be used to send the reading values to a

Go2Py/robot/model.py

@@ -82,7 +82,7 @@ class Go2Model:
         Calculates the inverse kinematics for the robot given a desired state.
 
         Args:
-            T (np.ndarray): The 4x4 homogenous transformation representing the pose of the base_link in the world frame
+            T (np.ndarray): The 4x4 homogeneous transformation representing the pose of the base_link in the world frame
             x (np.ndarray): A numpy array of size 12 representing foot positions in world frame in FR, FL, RR, RL order.
 
         Returns:

Go2Py/sim/gym/envs/base/curriculum.py

@@ -21,7 +21,7 @@ class Curriculum:
             self.grid <= high[:, None]
         ).all(axis=0)
 
-        assert len(inds) != 0, "You are intializing your distribution with an empty domain!"
+        assert len(inds) != 0, "You are initializing your distribution with an empty domain!"
 
         self.weights[inds] = value
 

Go2Py/sim/gym/envs/base/legged_robot.py

@@ -20,7 +20,7 @@ class LeggedRobot(BaseTask):
                  initial_dynamics_dict=None):
         """ Parses the provided config file,
             calls create_sim() (which creates, simulation, terrain and environments),
-            initilizes pytorch buffers used during training
+            initializes pytorch buffers used during training
 
         Args:
             cfg (Dict): Environment config file
@@ -513,7 +513,7 @@ class LeggedRobot(BaseTask):
             self.privileged_obs_buf.shape[1]}), you will discard data from the student!"
 
     def create_sim(self):
-        """ Creates simulation, terrain and evironments
+        """ Creates simulation, terrain and environments
         """
         self.up_axis_idx = 2  # 2 for z, 1 for y -> adapt gravity accordingly
         self.sim = self.gym.create_sim(
@@ -1123,7 +1123,7 @@ class LeggedRobot(BaseTask):
         Velocities are set to zero.
 
         Args:
-            env_ids (List[int]): Environemnt ids
+            env_ids (List[int]): Environment ids
         """
         self.dof_pos[env_ids] = self.default_dof_pos * \
             torch_rand_float(0.5, 1.5, (len(env_ids), self.num_dof), device=self.device)
@@ -1142,7 +1142,7 @@ class LeggedRobot(BaseTask):
             Sets base position based on the curriculum
             Selects randomized base velocities within -0.5:0.5 [m/s, rad/s]
         Args:
-            env_ids (List[int]): Environemnt ids
+            env_ids (List[int]): Environment ids
         """
         # base position
         if self.custom_origins:
@@ -1725,7 +1725,7 @@ class LeggedRobot(BaseTask):
             curriculum.set_to(low=low, high=high)
 
     def _prepare_reward_function(self):
-        """ Prepares a list of reward functions, whcih will be called to compute the total reward.
+        """ Prepares a list of reward functions, which will be called to compute the total reward.
             Looks for self._reward_<REWARD_NAME>, where <REWARD_NAME> are names of all non zero reward scales in the cfg.
         """
         # reward containers
@@ -2187,7 +2187,7 @@ class LeggedRobot(BaseTask):
                 gymutil.draw_lines(sphere_geom, self.gym, self.viewer, self.envs[i], sphere_pose)
 
     def _init_height_points(self, env_ids, cfg):
-        """ Returns points at which the height measurments are sampled (in base frame)
+        """ Returns points at which the height measurements are sampled (in base frame)
 
         Returns:
             [torch.Tensor]: Tensor of shape (num_envs, self.num_height_points, 3)

Go2Py/sim/gym/envs/base/legged_robot_config.py

@@ -9,7 +9,7 @@ class Cfg(PrefixProto, cli=False):
         num_observations = 235
         num_scalar_observations = 42
         # if not None a privilige_obs_buf will be returned by step() (critic obs
-        # for assymetric training). None is returned otherwise
+        # for asymmetric training). None is returned otherwise
         num_privileged_obs = 18
         privileged_future_horizon = 1
         num_actions = 12
@@ -228,7 +228,7 @@ class Cfg(PrefixProto, cli=False):
         # merge bodies connected by fixed joints. Specific fixed joints can be
         # kept by adding " <... dont_collapse="true">
         collapse_fixed_joints = True
-        fix_base_link = False  # fixe the base of the robot
+        fix_base_link = False  # fix the base of the robot
         # see GymDofDriveModeFlags (0 is none, 1 is pos tgt, 2 is vel tgt, 3 effort)
         default_dof_drive_mode = 3
         self_collisions = 0  # 1 to disable, 0 to enable...bitwise filter

README.md

@@ -57,7 +57,7 @@ Follow through the steps here to [setup](docs/setup.md) the robot and Go2Py.
 A set of examples and tutorials are provided to get you up and running quickly:
 
 - [Communicating with the robot](examples/00-robot-interface.ipynb) 
-- [Interracting with ROS2](examples/01-ros2-tools.ipynb) 
+- [Interacting with ROS2](examples/01-ros2-tools.ipynb) 
 - [Simulating with MuJoCo](examples/02-MuJoCo-sim.ipynb)
 - [Robot dynamics and kinematics](examples/03-robot-dynamic-model.ipynb)
 - [Finite state machine in low-level control](examples/04-FSM.ipynb) 

deploy/ros2_nodes/sportmode_nav2/params/ros_ekf.yaml

@@ -111,7 +111,7 @@ ekf_filter_node:
         odom0_differential: false
 
 # [ADVANCED] When the node starts, if this parameter is true, then the first measurement is treated as a "zero point"
-# for all future measurements. While you can achieve the same effect with the differential paremeter, the key
+# for all future measurements. While you can achieve the same effect with the differential parameter, the key
 # difference is that the relative parameter doesn't cause the measurement to be converted to a velocity before
 # integrating it. If you simply want your measurements to start at 0 for a given sensor, set this to true.
         odom0_relative: true

scripts/run_dev.sh

@@ -85,7 +85,7 @@ fi
 # Check if git-lfs is installed.
 git lfs &>/dev/null
 if [[ $? -ne 0 ]] ; then
-    print_error "git-lfs is not insalled. Please make sure git-lfs is installed before you clone the repo."
+    print_error "git-lfs is not installed. Please make sure git-lfs is installed before you clone the repo."
     exit 1
 fi
 
@@ -115,7 +115,7 @@ if [ "$(docker ps -a --quiet --filter status=exited --filter name=$CONTAINER_NAM
     docker rm $CONTAINER_NAME > /dev/null
 fi
 
-# Re-use existing container.
+# Reuse existing container.
 if [ "$(docker ps -a --quiet --filter status=running --filter name=$CONTAINER_NAME)" ]; then
     print_info "Attaching to running container: $CONTAINER_NAME"
     docker exec -i -t -u admin --workdir /workspaces/Go2Py $CONTAINER_NAME /bin/bash $@