Hi @ethanabrooks. currently i am working with HSR for reinforcement learning. i have got a lot of insight from your code. I have tried to run your code by using SAC for stable-baseline frameworks, it spent very long time but it was difficult to get the optimum behavior. However, i do not understand how do you calculate and define the reward for pick and place problem(hsr-env). What kind of reinforcement learning algorithm that you used for this environment?
how long did you spend to get the converge results for this environment?
i saw your another repository of HSR environment and i understand how did you define the reward and negative reward, but the repository is quite old. https://github.com/ethanabrooks/hsr
can you explain to me how do you define the reward in this "hsr-env"
Hi @ethanabrooks. currently i am working with HSR for reinforcement learning. i have got a lot of insight from your code. I have tried to run your code by using SAC for stable-baseline frameworks, it spent very long time but it was difficult to get the optimum behavior. However, i do not understand how do you calculate and define the reward for pick and place problem(hsr-env). What kind of reinforcement learning algorithm that you used for this environment?
how long did you spend to get the converge results for this environment?
i saw your another repository of HSR environment and i understand how did you define the reward and negative reward, but the repository is quite old. https://github.com/ethanabrooks/hsr
can you explain to me how do you define the reward in this "hsr-env"