Manipulation planning with caging grasps

2009 IEEE International Conference on Robotics and Automation, 2009

2010 IEEE International Conference on Robotics and Automation, 2010

IEEE Robotics &amp amp amp Automation Magazine

In this work, we present an integrated approach for planning collision-free grasping motions. The proposed Grasp–RRT planner combines the three main tasks needed for grasping an object: building a feasible grasp, solving the inverse kinematics problem and determining a collision-free trajectory that brings the hand to the grasping pose. Therefore, RRT-based algorithms are used to build a tree of reachable and collision-free configurations. During the tree generation, both grasp hypotheses and approach movements toward them are computed. The quality of reachable grasping poses is evaluated using grasp wrench space analysis. We present an extension to a dual arm planner which generates bimanual grasps together with collision-free dual arm grasping motions. The algorithms are evaluated with different setups in simulation and on the humanoid robot ARMAR-III.

2015

ArXiv, 2016

In this paper we propose an approach for efficient grasp selection for manipulation tasks of unknown objects. Even for simple tasks such as pick-and-place, a unique solution is rare to occur. Rather, multiple candidate grasps must be considered and (potentially) tested till a successful, kinematically feasible path is found. To make this process efficient, the grasps should be ordered such that those more likely to succeed are tested first. We propose to use grasp manipulability as a metric to prioritize grasps. We present results of simulation experiments which demonstrate the usefulness of our metric. Additionally, we present experiments with our physical robot performing simple manipulation tasks with a small set of different household objects.

arXiv (Cornell University), 2022

International Conference on Robotics and Automation, 2007

This paper presents the ResolveSpatialConstraints (RSC) algorithm for manipulation planning in a domain with movable obstacles. Empirically we show that our algorithm quickly generates plans for simulated articulated robots in a highly nonlinear search space of exponential dimension. RSC is a reverse-time search that samples future robot actions and constrains the space of prior object displacements. To optimize the efficiency

Algorithmic Foundations of …, 2004

Fundamentals of Leadership: Understanding the Basics and Rudiments of Leadership, 2024

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Coloration Technology, 2005