
This work presents an optimization approach based on non-impulsive contact-implicit path planning to effectively guide the joints of a snake robot called COBRA for object manipulation tasks.


coremsg

optimization-based-loco-manipulation-with-nonimpulsive-contact-implicit-planning-in-a-slithering-robot


Optimization-Based Loco-Manipulation with Nonimpulsive Contact-Implicit Planning in a Slithering Robot


title_rewrite


The paper proposes a novel Hessian approximation for Maximum a Posteriori estimation problems in robotics involving Gaussian mixture likelihoods, which leads to better convergence properties compared to previous approaches.


improving-hessian-approximation-for-gaussian-mixture-likelihoods-in-nonlinear-least-squares-optimization


Improving Hessian Approximation for Gaussian Mixture Likelihoods in Nonlinear Least Squares Optimization



The authors propose a novel distributed feedback optimization law, called AGGREGATIVE TRACKING FEEDBACK, to steer a network of agents to a stationary point of an aggregative optimization problem with possibly nonconvex objective functions.


distributed-feedback-optimization-for-aggregative-cooperative-robotics-with-nonconvex-objectives


Distributed Feedback Optimization for Aggregative Cooperative Robotics with Nonconvex Objectives
