scispace - formally typeset
Open AccessProceedings ArticleDOI

Pushing using compliance

Reads0
Chats0
TLDR
This paper presents an approach based on the rapidly-exploring random tree (RRT) algorithm that, besides paths through the open space, exploits the power of compliance.
Abstract
This paper addresses the problem of maneuvering an object by pushing it through an environment with obstacles. Instead of only pushing the object through open spaces, we also allow it to use compliance, e.g. allowing it to slide along obstacle boundaries. The advantage of using compliance is twofold: compliance does not only extend the number of situations in which a push plan can be found, it also allows for simpler (i.e. less complicated) paths in many cases. Here, we present an approach based on the rapidly-exploring random tree (RRT) algorithm that, besides paths through the open space, exploits the power of compliance

read more

Content maybe subject to copyright    Report

Figures
Citations
More filters
Journal ArticleDOI

Push-manipulation of complex passive mobile objects using experimentally acquired motion models

TL;DR: This work presents an experience-based push-manipulation approach that enables the robot to acquire experimental models regarding how pushable real world objects with complex 3D structures move in response to various pushing actions and demonstrates the superiority of the achievable planning and execution concept through safe and successful push- manipulation of a variety of passively mobile pushable objects.
Proceedings ArticleDOI

Automatic learning of pushing strategy for delivery of irregular-shaped objects

TL;DR: A learning-based approach for pushing objects of any irregular shape to user-specified goal locations by automatically collecting a set of data on how an irregular-shaped object moves given the robot's relative position and pushing direction.
Journal Article

Integer programming, lattices, and results in fixed dimension

TL;DR: In this article, various lattice basis reduction algorithms are used as auxiliary algorithms when solving integer feasibility and optimization problems, and three algorithms are described: binary search, a linear algorithm for a fixed number of constraints, and a randomized algorithm for different numbers of constraints.
Proceedings ArticleDOI

Achievable push-manipulation for complex passive mobile objects using past experience

TL;DR: The RRT algorithm is modified in such a way to use the recalled robot and object trajectories as building blocks to generate achievable and collision-free push plans that reliably transport the object to a desired 3 DoF pose.
Book ChapterDOI

Planning and Resilient Execution of Policies For Manipulation in Contact with Actuation Uncertainty

TL;DR: In this paper, a sampling-based motion planner is proposed for planning motion for robots with actuation uncertainty that incorporates contact with the environment and the compliance of the robot to reliably perform manipulation tasks.
References
More filters
Book

Numerical Analysis

TL;DR: This report contains a description of the typical topics covered in a two-semester sequence in Numerical Analysis, and describes the accuracy, efficiency and robustness of these algorithms.
Journal ArticleDOI

Multidimensional binary search trees used for associative searching

TL;DR: The multidimensional binary search tree (or k-d tree) as a data structure for storage of information to be retrieved by associative searches is developed and it is shown to be quite efficient in its storage requirements.
MonographDOI

Planning Algorithms: Introductory Material

TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Book

Planning Algorithms

Proceedings ArticleDOI

RRT-connect: An efficient approach to single-query path planning

TL;DR: A simple and efficient randomized algorithm is presented for solving single-query path planning problems in high-dimensional configuration spaces by incrementally building two rapidly-exploring random trees rooted at the start and the goal configurations.
Related Papers (5)