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

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)

Coordination of Multirobot Teams and Groups in Constrained Environments: Models, Abstractions, and Control Policies

Robots can augment and even replace humans in dangerous environments, such as search and rescue and reconnaissance missions, yet robots used in these situations are largely tele-operated. In most cases, the robots\u27 performance depends on the operator\u27s ability to control and coordinate the robots, resulting in increased response time and poor situational awareness, and hindering multirobot cooperation. Many factors impede extended autonomy in these situations, including the unique nature of individual tasks, the number of robots needed, the complexity of coordinating heterogeneous robot teams, and the need to operate safely. These factors can be partly addressed by having many inexpensive robots and by control policies that provide guarantees on convergence and safety. In this thesis, we address the problem of synthesizing control policies for navigating teams of robots in constrained environments while providing guarantees on convergence and safety. The approach is as follows. We first model the configuration space of the group (a space in which the robots cannot violate the constraints) as a set of polytopes. For a group with a common goal configuration, we reduce complexity by constructing a configuration space for an abstracted group state. We then construct a discrete representation of the configuration space, on which we search for a path to the goal. Based on this path, we synthesize feedback controllers, decentralized affine controllers for kinematic systems and nonlinear feedback controllers for dynamical systems, on the polytopes, sequentially composing controllers to drive the system to the goal. We demonstrate the use of this method in urban environments and on groups of dynamical systems such as quadrotors. We reduce the complexity of multirobot coordination by using an informed graph search to simultaneously build the configuration space and find a path in its discrete representation to the goal. Furthermore, by using an abstraction on groups of robots we dissociate complexity from the number of robots in the group. Although the controllers are designed for navigation in known environments, they are indeed more versatile, as we demonstrate in a concluding simulation of six robots in a partially unknown environment with evolving communication links, object manipulation, and stigmergic interactions

Cooperative Object Transport in Multi-robot Systems:A Review of the State-of-the-Art

In recent years, there has been a growing interest in designing multi-robot systems (hereafter MRSs) to provide cost effective, fault-tolerant and reliable solutions to a variety of automated applications. Here, we review recent advancements in MRSs specifically designed for cooperative object transport, which requires the members of MRSs to coordinate their actions to transport objects from a starting position to a final destination. To achieve cooperative object transport, a wide range of transport, coordination and control strategies have been proposed. Our goal is to provide a comprehensive summary for this relatively heterogeneous and fast-growing body of scientific literature. While distilling the information, we purposefully avoid using hierarchical dichotomies, which have been traditionally used in the field of MRSs. Instead, we employ a coarse-grain approach by classifying each study based on the transport strategy used; pushing-only, grasping and caging. We identify key design constraints that may be shared among these studies despite considerable differences in their design methods. In the end, we discuss several open challenges and possible directions for future work to improve the performance of the current MRSs. Overall, we hope to increase the visibility and accessibility of the excellent studies in the field and provide a framework that helps the reader to navigate through them more effectivelypublishersversionPeer reviewe

Goal Based Human Swarm Interaction for Collaborative Transport

Human-swarm interaction is an important milestone for the introduction of swarm-intelligence based solutions into real application scenarios. One of the main hurdles towards this goal is the creation of suitable interfaces for humans to convey the correct intent to multiple robots. As the size of the swarm increases, the complexity of dealing with explicit commands for individual robots becomes intractable. This brings a great challenge for the developer or the operator to drive robots to finish even the most basic tasks. In our work, we consider a different approach that humans specify only the desired goal rather than issuing individual commands necessary to obtain this task. We explore this approach in a collaborative transport scenario, where the user chooses the target position of an object, and a group of robots moves it by adapting themselves to the environment. The main outcome of this thesis is the design of integration of a collaborative transport behavior of swarm robots and an augmented reality human interface. We implemented an augmented reality (AR) application in which a virtual object is displayed overlapped on a detected target object. Users can manipulate the virtual object to generate the goal configuration for the object. The designed centralized controller translate the goal position to the robots and synchronize the state transitions. The whole system is tested on Khepera IV robots through the integration of Vicon system and ARGoS simulator

물체 수송을 위한 협업 로봇의 행동 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 이범희.This dissertation presents two cooperative object transportation techniques according to the characteristics of objects: passive and active. The passive object is a typical object, which cannot communicate with and detect other robots. The active object, however, has abilities to communicate with robots and can measure the distance from other robots using proximity sensors. Typical areas of research in cooperative object transportation include grasping, pushing, and caging techniques, but these require precise grasping behaviors, iterative motion correction according to the object pose, and the real-time acquisition of the object shape, respectively. For solving these problems, we propose two new object transportation techniques by considering the properties of objects. First, this dissertation presents a multi-agent behavior to cooperatively transport an active object using a sound signal and interactive communication. We first developed a sound localization method, which estimates the sound source from an active object by using three microphone sensors. Next, since the active object cannot be recalled by only a single robot, the robots organized a heterogeneous team by themselves with a pusher, a puller, and a supervisor. This self-organized team succeeded in moving the active object to a goal using the cooperation of its neighboring robots and interactive communication between the object and robots. Second, this dissertation presents a new cooperative passive object transportation technique using cyclic shift motion. The proposed technique does not need to consider the shape or the pose of objects, and equipped tools are also unnecessary for object transportation. Multiple robots create a parallel row formation using a virtual electric dipole field and then push multiple objects into the formation. This parallel row is extended to the goal using cyclic motion by the robots. The above processes are decentralized and activated based on the finite state machine of each robot. Simulations and practical experiments are presented to verify the proposed techniques.Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Related Work 4 1.2.1 The Categories of Object Transportation Techniques 4 1.2.2 Sound Localization Techniques for Active Object Transportation 7 1.3 Contributions 8 1.4 Organization 10 Chapter 2 Object Transportation Problem 11 2.1 Passive Object versus Active Object 11 2.2 Problem Formulation 13 2.3 Assumptions 13 Chapter 3 Active Object Transportation using a Sound Signal and Interactive Communication 15 3.1 Overview of Active Object Transportation 16 3.2 Sound Vector Generation using Triple Microphones 17 3.2.1 Sound Isocontour Generation using ILD 18 3.2.2 Sound Circle Generation using Inverse-square Law 21 3.2.3 Sound Vector Generation 22 3.3 Cooperative Control Method using Interactive Communication 25 3.3.1 Role Assignment of Multi-robot Team 25 3.3.2 Position Assignment of Multi-robot Team 26 3.3.3 Transportation Process of an Active Object 29 Chapter 4 Passive Object Transportation using Cyclic Shift Motion 33 4.1 Overview of Passive Object Transportation 34 4.2 Multi-robot Team Organization 35 4.3 Row Formation Generation using Multiple Robots 37 4.3.1 Cyclic Shift Motion 37 4.3.2 Path Generation using Virtual Electric Dipole Field 39 4.3.3 Path Following using Bang-bang Controller 42 4.4 Multi-object Transportation by a Decentralized Multi-robot Team 45 4.4.1 Information Acquisition Methods for Finite State Machine 45 4.4.2 Finite State Machines (FSMs) 48 4.4.2.1 The FSM of Guider Robots 49 4.4.2.2 The FSM of a Pusher Robot 52 4.4.2.3 The FSM of a Leader Robot 54 4.4.3 Object Transportation Process 55 4.4.4 Formation Constraints for Curved Transportation Path 57 Chapter 5 Simulation Results 61 5.1 Simulation Environment 61 5.2 Simulation Result of Passive Object Transportation 63 5.3 Comparison Results with Other Passive Object Transportation Techniques 69 5.3.1 Simulation Result of Leader-Follower Technique 70 5.3.2 Simulation Result of Caging Technique 72 Chapter 6 Practical Experiments 77 6.1 Experimental Environment 77 6.2 Experimental Results of Active Object Transportation 81 6.2.1 Experimental Result of the SV Estimation 81 6.2.2 Experimental Result of Active Object Transportation 82 6.3 Experimental Results of Passive Object Transportation 86 6.3.1 Small-object Transportation with Straight Path 86 6.3.2 Small-object Transportation with Curved Path 91 6.3.3 Large-object Transportation 93 6.4 Comparison Result with Caging Technique 95 Chapter 7 Discussion 96 Chapter 8 Conclusions 99 Appendix A: The Approaching Phase of Passive Object Transportation 101 A.1 Approaching Phase 101 A.2 Experimental Result of Approaching Phase 107 Appendix B: Object Transportation in a Static Environment 109 B.1 Overview 109 B.2 Object Transportation Problem in a Static Environment 111 B.3 Multi-object Transportation using Hybrid System 112 B.4 New Finite State Machines 113 B.4.1 The States of Guider Robots 114 B.4.2 The States of a Pusher Robot 115 B.4.3 The States of a Leader Robot 116 B.5 Simulation Results 118 B.5.1 Simulation Result: An Obstacle 118 B.5.2 Simulation Result: Two Obstacles 120 B.6 Practical Experiment 122 Bibliography 124Docto

3D Formation Control in Multi-Robot Teams Using Artificial Potential Fields

Multi-robot teams find applications in emergency response, search and rescue operations, convoy support and many more. Teams of autonomous aerial vehicles can also be used to protect a cargo of airplanes by surrounding them in some geometric shape. This research develops a control algorithm to attract UAVs to one or a set of bounded geometric shapes while avoiding collisions, re-configuring in the event of departure or addition of UAVs and maneuvering in mission space while retaining the configuration. Using potential field theory, weighted vector fields are described to attract UAVs to a desired formation. In order to achieve this, three vector fields are defined: one attracts UAVs located outside the formation towards bounded geometric shape; one pushes them away from the center towards the desired region and the third controls collision avoidance and dispersion of UAVs within the formation. The result is a control algorithm that is theoretically justified and verified using MATLAB which generates velocity vectors to attract UAVs to a loose formation and maneuver in the mission space while remaining in formation. This approach efficiently scales to different team sizes

The Design Of A Community-Informed Socially Interactive Humanoid Robot And End-Effectors For Novel Edge-Rolling

This dissertation discusses my work in building an HRI platform called Quori and my once separate now integrated work on a manipulation method that can enable robots like Quori, or any more capable robot, to move large circular cylindrical objects. Quori is a novel, affordable, socially interactive humanoid robot platform for facilitating non-contact human-robot interaction (HRI) research. The design of the system is motivated by feedback sampled from the HRI research community. The overall design maintains a balance of affordability and functionality. Ten Quori platforms have been awarded to a diverse group of researchers from across the United States to facilitate HRI research to build a community database from a common platform. This dissertation concludes with a demonstration of Quori transporting a large cylinder for which Quori does not have the power to lift nor the range of motion to dexterously manipulate. Quori is able to achieve this otherwise insurmountable task through a novel robotic manipulation technique called robotic edge-rolling. Edge-rolling refers to transporting a cylindrical object by rolling on its circular edge, as human workers maneuver a gas cylinder on the ground for example. This robotic edge-rolling is achieved by controlling the object to roll on the bottom edge in contact with the ground, and to slide on the surface of the robot\u27s end-effector. It can thus be regarded as a form of robotic dexterous, in-hand manipulation with nonprehensile grasps. This work mainly addresses the problem of grasp planning for edge-rolling by studying how to design appropriately shaped end-effectors with zero internal mobility and how to find feasible grasps for stably rolling the object with the simple end-effectors

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research