Added new teleoperation script + PushCubeLoop env + small refactoring of the environments.

What does this PR do:

Added new teleoperation script with LeRobot code in examples/teleoperate_leader_lerobot.py
Added new PushCubeLoop-v0 env in push_cube_loop_env.py to mimic the RL task currently used in LeRobot.
Added visualizations to PickPlace-v0 and PushCube-v0 in order to visualize the target region.
Added indexing to the cube and arm poses based on their body name in the sim in all envs rather than constant indices.
Added control decimation, i.e. multiple simulation steps per control step.
Improved the contact between gripper and cube by modifying the collision params in the description.

Fixed bug in teleoperation by sending control through mujoco rather than modifying joint in data.
Fixed index issue as after #33 the order of the robot and cubes was inverted so the indices of the joint and cube were completely wrong.
Fixed robot orientation. The new robot description added in #33 was rotated by 90 degrees so the robot was facing the cube in all environments.

In order to test the teleoperation you should:

Get the start_pos from the calibration done by LeRobot and change the values in examples/teleoperate_leader_lerobot.py. (can be found in .cache/calibration/koch/main_leader.json)

Run (use mjpython for mac):

python examples/teleoperate_leader_lerobot.py --device /dev/tty.usbmodem585A0078211 --env-name PushCubeLoop-v0

depending on your device and environment you'd like to test.

[ ] Validate action space: instead of absolute joint angle commands add a delta joint angle commands.
[ ] Validate reward function: debug reward function by trying to learn the tasks with LeRobot's tdmpc
[ ] Add sparse reward functions.