Motion Primitives and Planning for Robots with Closed Chain Systems and Changing Topologies

When operating in human environments, a robot should use predictable motions that allow humans to trust and anticipate its behavior. Heuristic search-based planning offers predictable motions and guarantees on completeness and sub-optimality of solutions. While search-based planning on motion primitive-based (lattice-based) graphs has been used extensively in navigation, application to high-dimensional state-spaces has, until recently, been thought impractical. This dissertation presents methods we have developed for applying these graphs to mobile manipulation, specifically for systems which contain closed chains. The formation of closed chains in tasks that involve contacts with the environment may reduce the number of available degrees-of-freedom but adds complexity in terms of constraints in the high-dimensional state-space. We exploit the dimensionality reduction inherent in closed kinematic chains to get efficient search-based planning. Our planner handles changing topologies (switching between open and closed-chains) in a single plan, including what transitions to include and when to include them. Thus, we can leverage existing results for search-based planning for open chains, combining open and closed chain manipulation planning into one framework. Proofs regarding the framework are introduced for the application to graph-search and its theoretical guarantees of optimality. The dimensionality-reduction is done in a manner that enables finding optimal solutions to low-dimensional problems which map to correspondingly optimal full-dimensional solutions. We apply this framework to planning for opening and navigating through non-spring and spring-loaded doors using a Willow Garage PR2. The framework motivates our approaches to the Atlas humanoid robot from Boston Dynamics for both stationary manipulation and quasi-static walking, as a closed chain is formed when both feet are on the ground

Versatile Multi-Contact Planning and Control for Legged Loco-Manipulation

Loco-manipulation planning skills are pivotal for expanding the utility of robots in everyday environments. These skills can be assessed based on a system's ability to coordinate complex holistic movements and multiple contact interactions when solving different tasks. However, existing approaches have been merely able to shape such behaviors with hand-crafted state machines, densely engineered rewards, or pre-recorded expert demonstrations. Here, we propose a minimally-guided framework that automatically discovers whole-body trajectories jointly with contact schedules for solving general loco-manipulation tasks in pre-modeled environments. The key insight is that multi-modal problems of this nature can be formulated and treated within the context of integrated Task and Motion Planning (TAMP). An effective bilevel search strategy is achieved by incorporating domain-specific rules and adequately combining the strengths of different planning techniques: trajectory optimization and informed graph search coupled with sampling-based planning. We showcase emergent behaviors for a quadrupedal mobile manipulator exploiting both prehensile and non-prehensile interactions to perform real-world tasks such as opening/closing heavy dishwashers and traversing spring-loaded doors. These behaviors are also deployed on the real system using a two-layer whole-body tracking controller

Behavior Trees in Robotics and AI: An Introduction

A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game. BTs are a very efficient way of creating complex systems that are both modular and reactive. These properties are crucial in many applications, which has led to the spread of BT from computer game programming to many branches of AI and Robotics. In this book, we will first give an introduction to BTs, then we describe how BTs relate to, and in many cases generalize, earlier switching structures. These ideas are then used as a foundation for a set of efficient and easy to use design principles. Properties such as safety, robustness, and efficiency are important for an autonomous system, and we describe a set of tools for formally analyzing these using a state space description of BTs. With the new analysis tools, we can formalize the descriptions of how BTs generalize earlier approaches. We also show the use of BTs in automated planning and machine learning. Finally, we describe an extended set of tools to capture the behavior of Stochastic BTs, where the outcomes of actions are described by probabilities. These tools enable the computation of both success probabilities and time to completion

경첩문을 여는 비행 매니퓰레이터에 대한 모델 예측 제어

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 기계항공공학부, 2020. 8. 김현진.From aerial pick-and-place to aerial transportation, aerial manipulation has been extensively studied in recent years thanks to its mobility and dexterity, each of which is a merit of an aerial vehicle and a robotic arm. However, to fully harness the concept of aerial manipulation, more complex tasks including interaction with movable structures should also be considered. Among various types of movable structures, this paper presents a multirotor-based aerial manipulator opening a daily-life moving structure, a hinged door. Two additional issues that would arise in interaction with a movable structure are addressed: 1) a constrained motion of the structure, and 2) collision avoidance with a moving structure. To handle these issues, we formulate a model predictive control (MPC) problem with a system dynamics constraint and state constraints for collision avoidance. A coupled system dynamics of a multirotor-based aerial manipulator and a hinged door is derived and later simplified for faster computation in MPC. State constraints for collision avoidance with itself, a door, and a doorframe are generated. By implementing a constrained version of differential dynamic programming (DDP), we can generate reference trajectories through MPC in real-time. The proposed method is validated through simulation results and experiments with a real-like hinged door in which a disturbance observer (DOB) based robust motion controller is employed.비행 매니퓰레이터는 3차원 공간 속에 빠르게 위치할 수 있는 비행체의 장점과 외부와의 상호작용이 가능한 로봇팔의 장점이 결합된 비행체로, 최근 물건 집고 옮기기부터 물품 운송까지 다양한 임무를 수행하기 위해 활발하게 연구되어 왔다. 그러나, 온전히 비행 매니퓰레이터의 가능성을 활용하기 위해서는 움직일 수 있는 외부 구조와의 상호작용과 같이 더욱 복잡한 임무 또한 수행할 수 있어야 할 것이다. 여러 종류의 움직일 수 있는 구조물 중 본 논문에서는 일상 속에서 쉽게 마주칠 수 있는 경첩문을 여는 멀티로터 기반의 비행 매니퓰레이터에 대해 제시한다. 정적인 구조물과의 상호작용과는 달리 동적인 구조물과의 상호작용에 있어서 발생할 수 있는 1) 구조물의 제약된 움직임, 그리고 2) 움직이는 구조물과의 충돌 회피의 2가지 추가적인 문제에 대해 다루었다. 이러한 문제를 다루기 위해 모델 예측 제어 (MPC)를 적용하였으며, 시스템 동역학에 대한 제약조건 및 충돌 회피에 대한 제약 조건을 부여하였다. 멀티로터 기반의 비행 매니퓰레이터와 경첩문의 결합 시스템에 대한 동역학을 유도하였으며, 이후 모델 예측 제어에서의 빠른 계산 속도를 위해 단순화되었다. 충돌 회피에 대한 제약 조건은 모두 상태 변수로 표현되었으며, 비행 매니퓰레이터의 멀티로터 프레임과 로봇팔 사이의 충돌 (자기 충돌), 문과의 충돌, 그리고 문틀과의 충돌을 고려하였다. 미분 기반의 동적 프로그래밍 기법 (differential dynamic programming)에 제약조건이 고려된 알고리즘을 구현함으로써 모델 기반 예측 제어를 통해 실시간으로 경로를 계획할 수 있다. 제안된 방법은 시뮬레이션과 실제 크기의 문을 활용한 실험을 통해 검증되었으며, 외란 관측기 기반의 강건 제어 기법이 실험에 활용되었다.1 Introduction 1 1.1 Literature review 2 1.2 Thesis contribution 3 1.3 Thesis outline 3 2 Equations of motion 4 2.1 Assumption 4 2.2 Kinematics 5 2.3 Dynamics 6 2.4 Simpli ed dynamics 8 3 Model predictive control 10 3.1 Problem formulation 10 3.1.1 Objective function 11 3.1.2 Hard constraints 11 3.2 Collision avoidance constraints 11 3.2.1 Self collision avoidance 13 3.2.2 Door collision avoidance 13 3.2.3 Doorframe collision avoidance 14 3.3 Optimal control solver 14 3.3.1 Differential dynamic programming 14 3.3.2 DDP with augmented Lagrangian method 15 4 Experimental setup 17 4.1 Door state estimation 17 4.2 Multirotor robust controller 18 4.3 Hardware setup 19 5 Results 20 5.1 Simulation results 20 5.2 Experimental results 25 6 Conclusion 29Maste

Mobile Manipulation with a Kinematically Redundant Manipulator for a Pick-and-Place Scenario

Mobile robots and robotic manipulators have traditionally been used separately performing different types of tasks. For example, industrial robots have typically been programmed to follow trajectories using position sensors. If combining the two types of robots and adding sensors new possibilities emerge. This enables new applications, but it also raises the question of how to combine the sensors and the added kinematic complexity. An omni-directional mobile robot together with a new type of kinematically redundant manipulator for future use as a service robot for grocery stores is proposed. The scenario is that of distributing groceries on refilling shelves, and a constraint- based task specification methodology to incorporate sensors and geometric uncertainties into the task is employed. Sensor fusion is used to estimate the pose of the mobile base online. Force sensors are utilized to resolve remaining uncertainties. The approach is verified with experiments

Human-friendly robotic manipulators: safety and performance issues in controller design

Recent advances in robotics have spurred its adoption into new application areas such as medical, rescue, transportation, logistics, personal care and entertainment. In the personal care domain, robots are expected to operate in human-present environments and provide non-critical assistance. Successful and flourishing deployment of such robots present different opportunities as well as challenges. Under a national research project, Bobbie, this dissertation analyzes challenges associated with these robots and proposes solutions for identified problems. The thesis begins by highlighting the important safety concern and presenting a comprehensive overview of safety issues in a typical domestic robot system. By using functional safety concept, the overall safety of the complex robotic system was analyzed through subsystem level safety issues. Safety regions in the world model of the perception subsystem, dependable understanding of the unstructured environment via fusion of sensory subsystems, lightweight and compliant design of mechanical components, passivity based control system and quantitative metrics used to assert safety are some important points discussed in the safety review. The main research focus of this work is on controller design of robotic manipulators against two conflicting requirements: motion performance and safety. Human-friendly manipulators used on domestic robots exhibit a lightweight design and demand a stable operation with a compliant behavior injected via a passivity based impedance controller. Effective motion based manipulation using such a controller requires a highly stiff behavior while important safety requirements are achieved with compliant behaviors. On the basis of this intuitive observation, this research identifies suitable metrics to identify the appropriate impedance for a given performance and safety requirement. This thesis also introduces a domestic robot design that adopts a modular design approach to minimize complexity, cost and development time. On the basis of functional modularity concept where each module has a unique functional contribution in the system, the robot “Bobbie-UT‿ is built as an interconnection of interchangeable mobile platform, torso, robotic arm and humanoid head components. Implementation of necessary functional and safety requirements, design of interfaces and development of suitable software architecture are also discussed with the design