Semi-Infinite Programming’s Application in Robotics
Date:
In optimization theory, semi-infinite programming (SIP) is an optimization problem with a finite number of variables and an infinite number of constraints, or an infinite number of variables and a finite number of constraints. In this talk, I will introduce our work which uses SIP to solve the problems in the field of robotics.
In the semi-infinite program with complementarity constraints (SIPCC) work, we use SIP to address the problem that contact is an infinite phenomenon involving continuous regions of interaction. Our method enables a gripper to find a feasible pose to hold (non-)convex objects while ensuring force and torque balance. In the non-penetration iterative closest points for single-view multi-object 6D pose estimation work, we use SIP to solve the penetration between (non-)convex objects. Through introducing non-penetration constraints to the framework of iterative closest points (ICP), we improve the pose estimation result’s accuracy of deep neural network based methods. Also, our method outperforms the best result on the IC-BIN dataset in the Benchmark for 6D Object Pose Estimation.