  This paper provides a brief overview of our submission to the no interaction
track of SAPIEN ManiSkill Challenge 2021. Our approach follows an end-to-end
pipeline which mainly consists of two steps: we first extract the point cloud
features of multiple objects; then we adopt these features to predict the
action score of the robot simulators through a deep and wide transformer-based
network. More specially, %to give guidance for future work, to open up avenues
for exploitation of learning manipulation skill, we present an empirical study
that includes a bag of tricks and abortive attempts. Finally, our method
achieves a promising ranking on the leaderboard. All code of our solution is
available at https://github.com/liu666666/bigfish\_codes.
