End-effector vibrations reduction in trajectory tracking for mobile manipulator

A method of motion planning for a mobile manipulator taking into account damping the end-effector vibrations is presented. The primary task of the robot is to trace a given end-effector trajectory. The redundant degrees of freedom are used to fulfil secondary objectives such as minimisation of platform kinetic energy and maximisation of holonomic manipulability measure, which leads to reduction of the end-effector vibrations. The method is based on Jacobian pseudo inverse at the acceleration level. Nonholonomic constraints in a Pfaffian form are explicitly incorporated to the control algorithm. A computer example involving a mobile manipulator consisting of a nonholonomic platform (2, 0) class and SCARA-type holonomic manipulator operating in two-dimensional task space is also presented

Challenges and Solutions for Autonomous Robotic Mobile Manipulation for Outdoor Sample Collection

In refinery, petrochemical, and chemical plants, process technicians collect uncontaminated samples to be analyzed in the quality control laboratory all time and all weather. This traditionally manual operation not only exposes the process technicians to hazardous chemicals, but also imposes an economical burden on the management. The recent development in mobile manipulation provides an opportunity to fully automate the operation of sample collection. This paper reviewed the various challenges in sample collection in terms of navigation of the mobile platform and manipulation of the robotic arm from four aspects, namely mobile robot positioning/attitude using global navigation satellite system (GNSS), vision-based navigation and visual servoing, robotic manipulation, mobile robot path planning and control. This paper further proposed solutions to these challenges and pointed the main direction of development in mobile manipulation

기구학적 및 동적 제한조건들을 고려한 모바일 매니퓰레이터의 작업 중심 전신 동작 생성 전략

학위논문(박사) -- 서울대학교대학원 : 융합과학기술대학원 융합과학부(지능형융합시스템전공), 2023. 2. 박재흥.모바일 매니퓰레이터는 모바일 로봇에 장착된 매니퓰레이터입니다. 모바일 매니퓰레이터는 고정형 매니퓰레이터에 비해 모바일 로봇의 이동성을 제공받기 때문에 다양하고 복잡한 작업을 수행할 수 있습니다. 그러나 두 개의 서로 다른 시스템을 결합함으로써 모바일 매니퓰레이터의 전신을 계획하고 제어할 때 여러 특징을 고려해야 합니다. 이러한 특징들은 여자유도, 두 시스템의 관성 차이 및 모바일 로봇의 비홀로노믹 제한 조건 등이 있습니다. 본 논문의 목적은 기구학적 및 동적 제한조건들을 고려하여 모바일 매니퓰레이터의 전신 동작 생성 전략을 제안하는 것입니다. 먼저, 모바일 매니퓰레이터가 초기 위치에서 문을 통과하여 목표 위치에 도달하기 위한 전신 경로를 계산하는 프레임워크를 제안합니다. 이 프레임워크는 로봇과 문에 의해 생기는 기구학적 제한조건을 고려합니다. 제안하는 프레임워크는 두 단계를 거쳐 전신의 경로를 얻습니다. 첫 번째 단계에서는 그래프 탐색 알고리즘을 이용하여 모바일 로봇의 자세 경로와 문의 각도 경로를 계산합니다. 특히, 그래프 탐색에서 area indicator라는 정수 변수를 상태의 구성 요소로서 정의하는데, 이는 문에 대한 모바일 로봇의 상대적 위치를 나타냅니다. 두 번째 단계에서는 모바일 로봇의 경로와 문의 각도를 통해 문의 손잡이 위치를 계산하고 역기구학을 활용하여 매니퓰레이터의 관절 위치를 계산합니다. 제안된 프레임워크의 효율성은 비홀로노믹 모바일 매니퓰레이터를 사용한 시뮬레이션 및 실제 실험을 통해 검증되었습니다. 둘 째, 최적화 방법을 기반으로한 전신 제어기를 제안합니다. 이 방법은 등식 및 부등식 제한조건 모두에 대해 가중 행렬을 반영한 계층적 최적화 문제의 해를 계산합니다. 이 방법은 모바일 매니퓰레이터 또는 휴머노이드와 같이 자유도가 많은 로봇의 여자유도를 해결하기 위해 개발되어 작업 우선 순위에 따라 가중치가 다른 관절 동작으로 여러 작업을 수행할 수 있습니다. 제안된 방법은 가중 행렬을 최적화 문제의 1차 최적 조건을 만족하도록 하며, Active-set 방법을 활용하여 등식 및 부등식 작업을 처리합니다. 또한, 대칭적인 영공간 사영 행렬을 사용하여 계산상 효율적입니다. 결과적으로, 제안된 제어기를 활용하는 로봇은 우선 순위에 따라 개별적인 관절 가중치를 반영하여 전신 움직임을 효과적으로 보여줍니다. 제안된 제어기의 효용성은 모바일 매니퓰레이터와 휴머노이드를 이용한 실험을 통해 검증하였습니다. 마지막으로, 모바일 매니퓰레이터의 동적 제한조건들 중 하나로서 자가 충돌 회피 알고리즘을 제안합니다. 제안된 방법은 매니퓰레이터와 모바일 로봇 간의 자가 충돌에 중점을 둡니다. 모바일 로봇의 버퍼 영역을 둘러싸는 3차원 곡면인 distance buffer border의 개념을 정의합니다. 버퍼 영역의 두께는 버퍼 거리입니다. 매니퓰레이터와 모바일 로봇 사이의 거리가 버퍼 거리보다 작은 경우, 즉 매니퓰레이터가 모바일 로봇의 버퍼 영역 내부에 있는 경우 제안된 전략은 매니퓰레이터를 버퍼 영역 밖으로 내보내기 위해 모바일 로봇의 움직임을 생성합니다. 따라서 매니퓰레이터는 미리 정의된 매니퓰레이터의 움직임을 수정하지 않고도 모바일 로봇과의 자가 충돌을 피할 수 있습니다. 모바일 로봇의 움직임은 가상의 힘을 가함으로써 생성됩니다. 특히, 힘의 방향은 차동 구동 이동 로봇의 비홀로노믹 제약 및 조작기의 도달 가능성을 고려하여 결정됩니다. 제안된 알고리즘은 7자유도 로봇팔을 가진 차동 구동 모바일 로봇에 적용하여 다양한 실험 시나리오에서 입증되었습니다.A mobile manipulator is a manipulator mounted on a mobile robot. Compared to a fixed-base manipulator, the mobile manipulator can perform various and complex tasks because the mobility is offered by the mobile robot. However, combining two different systems causes several features to be considered when generating the whole-body motion of the mobile manipulator. The features include redundancy, inertia difference, and non-holonomic constraint. The purpose of this thesis is to propose the whole-body motion generation strategy of the mobile manipulator for considering kinematic and dynamic constraints. First, a planning framework is proposed that computes a path for the whole-body configuration of the mobile manipulator to navigate from the initial position, traverse through the door, and arrive at the target position. The framework handles the kinematic constraint imposed by the closed-chain between the robot and door. The proposed framework obtains the path of the whole-body configuration in two steps. First, the path for the pose of the mobile robot and the path for the door angle are computed by using the graph search algorithm. In graph search, an integer variable called area indicator is introduced as an element of state, which indicates where the robot is located relative to the door. Especially, the area indicator expresses a process of door traversal. In the second step, the configuration of the manipulator is computed by the inverse kinematics (IK) solver from the path of the mobile robot and door angle. The proposed framework has a distinct advantage over the existing methods that manually determine several parameters such as which direction to approach the door and the angle of the door required for passage. The effectiveness of the proposed framework was validated through experiments with a nonholonomic mobile manipulator. Second, a whole-body controller is presented based on the optimization method that can consider both equality and inequality constraints. The method computes the optimal solution of the weighted hierarchical optimization problem. The method is developed to resolve the redundancy of robots with a large number of Degrees of Freedom (DOFs), such as a mobile manipulator or a humanoid, so that they can execute multiple tasks with differently weighted joint motion for each task priority. The proposed method incorporates the weighting matrix into the first-order optimality condition of the optimization problem and leverages an active-set method to handle equality and inequality constraints. In addition, it is computationally efficient because the solution is calculated in a weighted joint space with symmetric null-space projection matrices for propagating recursively to a low priority task. Consequently, robots that utilize the proposed controller effectively show whole-body motions handling prioritized tasks with differently weighted joint spaces. The effectiveness of the proposed controller was validated through experiments with a nonholonomic mobile manipulator as well as a humanoid. Lastly, as one of dynamic constraints for the mobile manipulator, a reactive self-collision avoidance algorithm is developed. The proposed method mainly focuses on self-collision between a manipulator and the mobile robot. We introduce the concept of a distance buffer border (DBB), which is a 3D curved surface enclosing a buffer region of the mobile robot. The region has the thickness equal to buffer distance. When the distance between the manipulator and mobile robot is less than the buffer distance, i.e. the manipulator lies inside the buffer region of the mobile robot, the proposed strategy is to move the mobile robot away from the manipulator in order for the manipulator to be placed outside the border of the region, the DBB. The strategy is achieved by exerting force on the mobile robot. Therefore, the manipulator can avoid self-collision with the mobile robot without modifying the predefined motion of the manipulator in a world Cartesian coordinate frame. In particular, the direction of the force is determined by considering the non-holonomic constraint of the differentially driven mobile robot. Additionally, the reachability of the manipulator is considered to arrive at a configuration in which the manipulator can be more maneuverable. To realize the desired force and resulting torque, an avoidance task is constructed by converting them into the accelerations of the mobile robot and smoothly inserted with a top priority into the controller. The proposed algorithm was implemented on a differentially driven mobile robot with a 7-DOFs robotic arm and its performance was demonstrated in various experimental scenarios.1 INTRODUCTION 1 1.1 Motivation 1 1.2 Contributions of thesis 2 1.3 Overview of thesis 3 2 WHOLE-BODY MOTION PLANNER : APPLICATION TO NAVIGATION INCLUDING DOOR TRAVERSAL 5 2.1 Background & related works 7 2.2 Proposed framework 9 2.2.1 Computing path for mobile robot and door angle - S1 10 2.2.1.1 State 10 2.2.1.2 Action 13 2.2.1.3 Cost 15 2.2.1.4 Search 18 2.2.2 Computing path for arm configuration - S2 20 2.3 Results 21 2.3.1 Application to pull and push-type door 21 2.3.2 Experiment in cluttered environment 22 2.3.3 Experiment with different robot platform 23 2.3.4 Comparison with separate planning by existing works 24 2.3.5 Experiment with real robot 29 2.4 Conclusion 29 3 WHOLE-BODY CONTROLLER : WEIGHTED HIERARCHICAL QUADRATIC PROGRAMMING 31 3.1 Related works 32 3.2 Problem statement 34 3.2.1 Pseudo-inverse with weighted least-squares norm for each task 35 3.2.2 Problem statement 37 3.3 WHQP with equality constraints 37 3.4 WHQP with inequality constraints 45 3.5 Experimental results 48 3.5.1 Simulation experiment with nonholonomic mobile manipulator 48 3.5.1.1 Scenario description 48 3.5.1.2 Task and weighting matrix description 49 3.5.1.3 Results 51 3.5.2 Real experiment with nonholonomic mobile manipulator 53 3.5.2.1 Scenario description 53 3.5.2.2 Task and weighting matrix description 53 3.5.2.3 Results 54 3.5.3 Real experiment with humanoid 55 3.5.3.1 Scenario description 55 3.5.3.2 Task and weighting matrix description 55 3.5.3.3 Results 57 3.6 Discussions and implementation details 57 3.6.1 Computation cost 57 3.6.2 Composite weighting matrix in same hierarchy 59 3.6.3 Nullity of WHQP 59 3.7 Conclusion 59 4 WHOLE-BODY CONSTRAINT : SELF-COLLISION AVOIDANCE 61 4.1 Background & related Works 64 4.2 Distance buffer border and its score computation 65 4.2.1 Identification of potentially colliding link pairs 66 4.2.2 Distance buffer border 67 4.2.3 Evaluation of distance buffer border 69 4.2.3.1 Singularity of the differentially driven mobile robot 69 4.2.3.2 Reachability of the manipulator 72 4.2.3.3 Score of the DBB 74 4.3 Self-collision avoidance algorithm 75 4.3.1 Generation of the acceleration for the mobile robot 76 4.3.2 Generation of the repulsive acceleration for the other link pair 82 4.3.3 Construction of an acceleration-based task for self-collision avoidance 83 4.3.4 Insertion of the task in HQP-based controller 83 4.4 Experimental results 86 4.4.1 System overview 87 4.4.2 Experimental results 87 4.4.2.1 Self-collision avoidance while tracking the predefined trajectory 87 4.4.2.2 Self-collision avoidance while manually guiding the end-effector 89 4.4.2.3 Extension to obstacle avoidance when opening the refrigerator 91 4.4.3 Discussion 94 4.5 Conclusion 95 5 CONCLUSIONS 97 Abstract (In Korean) 113 Acknowlegement 116박

Enhanced online programming for industrial robots

The use of robots and automation levels in the industrial sector is expected to grow, and is driven by the on-going need for lower costs and enhanced productivity. The manufacturing industry continues to seek ways of realizing enhanced production, and the programming of articulated production robots has been identified as a major area for improvement. However, realizing this automation level increase requires capable programming and control technologies. Many industries employ offline-programming which operates within a manually controlled and specific work environment. This is especially true within the high-volume automotive industry, particularly in high-speed assembly and component handling. For small-batch manufacturing and small to medium-sized enterprises, online programming continues to play an important role, but the complexity of programming remains a major obstacle for automation using industrial robots. Scenarios that rely on manual data input based on real world obstructions require that entire production systems cease for significant time periods while data is being manipulated, leading to financial losses. The application of simulation tools generate discrete portions of the total robot trajectories, while requiring manual inputs to link paths associated with different activities. Human input is also required to correct inaccuracies and errors resulting from unknowns and falsehoods in the environment. This study developed a new supported online robot programming approach, which is implemented as a robot control program. By applying online and offline programming in addition to appropriate manual robot control techniques, disadvantages such as manual pre-processing times and production downtimes have been either reduced or completely eliminated. The industrial requirements were evaluated considering modern manufacturing aspects. A cell-based Voronoi generation algorithm within a probabilistic world model has been introduced, together with a trajectory planner and an appropriate human machine interface. The robot programs so achieved are comparable to manually programmed robot programs and the results for a Mitsubishi RV-2AJ five-axis industrial robot are presented. Automated workspace analysis techniques and trajectory smoothing are used to accomplish this. The new robot control program considers the working production environment as a single and complete workspace. Non-productive time is required, but unlike previously reported approaches, this is achieved automatically and in a timely manner. As such, the actual cell-learning time is minimal

Learning Probabilistic Generative Models For Fast Sampling-Based Planning

Due to their simplicity and efficiency in high dimensional space, sampling-based motion planners have been gaining interest for robotic manipulation in recent years. We present several new learning approaches using probabilistic generative models for fast sampling-based planning. First, we propose fast collision detection in high dimensional configuration spaces based on Gaussian Mixture Models (GMMs) for Rapidly-exploring Random Trees (RRT). In addition, we introduce a new probabilistically safe local steering primitive based on the probabilistic model. Our local steering procedure is based on a new notion of a convex probabilistically safety corridor that is constructed around a configuration using tangent hyperplanes of confidence ellipsoids of GMMs learned from prior collision history. For efficient sampling, we suggest a sampling method with a learned Q-function with linear function approximation based on feature representations such as Radial Basis Functions. This sampling method chooses the optimal node from which to extend the search tree via the softmax function of learned state values. We also discuss a novel constrained sampling-based motion planning method for grasp and transport tasks with redundant robotic manipulators, which allows the best grasp configuration and approach direction to be automatically determined. Since these approaches with the learned probabilistic models require large size data and time for training, it is essential that they are able to be adapted to environmental change in an online manner. The suggested online learning approach with the Dirichlet Process Mixture Model (DPMM) can adapt the complexity to the data and learn new Gaussian clusters with streaming data in newly explored areas without batch learning. We have applied these approaches in a number of robot arm planning scenarios and have shown their utility and effectiveness in simulation and on a physical 7-DoF robot manipulator