论文标题
在接触率丰富的系统中进行偶然受限的优化，以进行牢固的操纵
Chance-Constrained Optimization in Contact-Rich Systems for Robust Manipulation
论文作者
论文摘要
本文为操纵过程中的稳健轨迹优化提供了偶然受限的公式。特别是，我们为随机离散时间线性互补系统（SDLC）提供了偶然受限的优化。为了解决优化问题，我们制定了使用机会约束（MIQPCC）的混合构成二次编程。在我们的表述中，我们明确考虑了互补性以及捕获动力学随机演变的联合机会限制。我们评估了在几种系统上模拟中优化轨迹的鲁棒性。所提出的方法的表现优于SDLC的鲁棒轨迹优化的一些最新方法。
This paper presents a chance-constrained formulation for robust trajectory optimization during manipulation. In particular, we present a chance-constrained optimization for Stochastic Discrete-time Linear Complementarity Systems (SDLCS). To solve the optimization problem, we formulate Mixed-Integer Quadratic Programming with Chance Constraints (MIQPCC). In our formulation, we explicitly consider joint chance constraints for complementarity as well as states to capture the stochastic evolution of dynamics. We evaluate robustness of our optimized trajectories in simulation on several systems. The proposed approach outperforms some recent approaches for robust trajectory optimization for SDLCS.
