14 research outputs found
Grasping and Assembling with Modular Robots
A wide variety of problems, from manufacturing to disaster response and space exploration, can benefit from robotic systems that can firmly grasp objects or assemble various structures, particularly in difficult, dangerous environments. In this thesis, we study the two problems, robotic grasping and assembly, with a modular robotic approach that can facilitate the problems with versatility and robustness.
First, this thesis develops a theoretical framework for grasping objects with customized effectors that have curved contact surfaces, with applications to modular robots. We present a collection of grasps and cages that can effectively restrain the mobility of a wide range of objects including polyhedra. Each of the grasps or cages is formed by at most three effectors. A stable grasp is obtained by simple motion planning and control. Based on the theory, we create a robotic system comprised of a modular manipulator equipped with customized end-effectors and a software suite for planning and control of the manipulator.
Second, this thesis presents efficient assembly planning algorithms for constructing planar target structures collectively with a collection of homogeneous mobile modular robots. The algorithms are provably correct and address arbitrary target structures that may include internal holes. The resultant assembly plan supports parallel assembly and guarantees easy accessibility in the sense that a robot does not have to pass through a narrow gap while approaching its target position. Finally, we extend the algorithms to address various symmetric patterns formed by a collection of congruent rectangles on the plane.
The basic ideas in this thesis have broad applications to manufacturing (restraint), humanitarian missions (forming airfields on the high seas), and service robotics (grasping and manipulation)
Quasi-static Soft Fixture Analysis of Rigid and Deformable Objects
We present a sampling-based approach to reasoning about the caging-based
manipulation of rigid and a simplified class of deformable 3D objects subject
to energy constraints. Towards this end, we propose the notion of soft fixtures
extending earlier work on energy-bounded caging to include a broader set of
energy function constraints and settings, such as gravitational and elastic
potential energy of 3D deformable objects. Previous methods focused on
establishing provably correct algorithms to compute lower bounds or
analytically exact estimates of escape energy for a very restricted class of
known objects with low-dimensional C-spaces, such as planar polygons. We
instead propose a practical sampling-based approach that is applicable in
higher-dimensional C-spaces but only produces a sequence of upper-bound
estimates that, however, appear to converge rapidly to actual escape energy. We
present 8 simulation experiments demonstrating the applicability of our
approach to various complex quasi-static manipulation scenarios. Quantitative
results indicate the effectiveness of our approach in providing upper-bound
estimates for escape energy in quasi-static manipulation scenarios. Two
real-world experiments also show that the computed normalized escape energy
estimates appear to correlate strongly with the probability of escape of an
object under randomized pose perturbation.Comment: Paper submitted to ICRA 202
Randomized Planning and Control Strategy for Whole-Arm Manipulation of a Slippery Polygonal Object
The present paper introduces a planning and control strategy for whole-arm manipulation of a slippery polygonal object. Randomized planning methods are first proposed in order to generate contact state transitions, which help not only to reduce the amount of calculation required, but also to handle a hybrid system composed of a continuous system and a discrete system, which has a large search space and complicated constraints. Second, a novel control strategy, which can switch manipulation modes among quasi-static, dynamic, and caging manipulation depending on the situation, is proposed. This strategy not only can cope with changes in the mechanics of the system caused by contact state transitions, but also can increase the manipulation feasibility and reliability. The validity of the proposed methods is verified through simulations and experiments
Two-finger squeezing caging of polygonal and polyhedral object
The problem of object caging is defined as a problem of designing a formation of fingers to restrict an object within a bounded space. Assuming two pointed fingers and a rigid polygonal or polyhedral object, this paper addresses the problem of two-finger squeezing caging, i.e., to characterize all possible formations of the fingers that are capable of caging the object via limiting their separation distance. Our study is done entirely in the object's frame allowing the object to be considered as a static obstacle so that the analysis can be performed in terms of the finger motion. Our solution is based on partitioning the configuration space of the problem into finite subsets called nodes. A graph of these nodes can then be constructed to represent all possible finger motion where a search based method can be applied to solve the caging problem. The partitioning of the configuration is based on convex decomposition of the free space. Let m be the number of convex subsets from the decomposition, our proposed algorithm reports all squeezing cage sets in O(n 2 +nm+m 2 log m) for a polygonal input with n vertices and O(nN 3 + n 2 + nm + m 2 log m) for a polyhedron with n vertices and having N edges exhibiting a reflex angle. After reporting all squeezing cages, the proposed algorithm can answer whether a given finger placement can cage the object within a logarithmic time
対象物体と指配置のコンフィグレーション空間を用いた不確かさを扱える効率的なケージング計画
学位の種別:課程博士University of Tokyo(東京大学
Capture and generalisation of close interaction with objects
Robust manipulation capture and retargeting has been a longstanding goal in both the
fields of animation and robotics. In this thesis I describe a new approach to capture
both the geometry and motion of interactions with objects, dealing with the problems
of occlusion by the use of magnetic systems, and performing the reconstruction of the
geometry by an RGB-D sensor alongside visual markers. This ‘interaction capture’
allows the scene to be described in terms of the spatial relationships between the character
and the object using novel topological representations such as the Electric Parameters,
which parametrise the outer space of an object using properties of the surface of
the object. I describe the properties of these representations for motion generalisation
and discuss how they can be applied to the problems of human-like motion generation
and programming by demonstration. These generalised interactions are shown
to be valid by demonstration of retargeting grasping and manipulation to robots with
dissimilar kinematics and morphology using only local, gradient-based planning