# What do the state features of KukaGymEnv represent?

I trying to use DDPG augmented with Hindsight Experience Replay (HER) on pybullet's KukaGymEnv.

To formulate the feature vector for the goal state, I need to know what the features of the state of the environment represent. To be precise, a typical state vector of KukaGymEnv is an object of the numpy.ndarray class with a shape of (9,).

What do each of these 8 elements represent, and how can I formulate the goal state vector for this environment? I tried going through the source code of the KukaGymEnv, but was unable to understand anything useful.

Here's an incomplete answer, but it may help.

Your state is read by the function getExtendedObservation(). This function makes two things : it calls the function getObservation() from this source code, gets a state, and extend this state with three components :

relative x,y position and euler angle of block in gripper space

But what are the 5 first components returned by getObservation()? From what I read, there are positions, then euler angles describing the orientation. But that would make 6 + 3 = 9 features, so there is either only 2 positions, or only 2 euler angles. You may know kuka better than me and know the answer of this one :).

So, to sum up :

state = [X, Y, (Z, ) , Alpha, Gamma, (Beta, ), gripX, gripY, gripAlpha]


(Either Z or Beta is absent)

• There's a mistake in the question. The state space for the environment is actually a 9 dimensional vector, in which case, your answer is correct. I ll rectify the typo right away. Thanks for the help! Aug 27 '20 at 10:38