Design of a Novel Long-Reach Cable-Driven Hyper-Redundant Snake-like Manipulator for Inspection and Maintenance

Robotic inspection and maintenance are gaining importance due to the number of different scenarios in which robots can operate. The use of robotic systems to accomplish such tasks has deep implications in terms of safety for human workers and can significantly extend the life of infrastructures and industrial facilities. In this context, long-reach cable-driven hyper-redundant robots can be employed to inspect areas that are difficult to reach and hazardous environments such as tanks and vessels. This paper presents a novel long-reach cable-driven hyper-redundant robot called SLIM (Snake-Like manipulator for Inspection and Maintenance). SLIM consists of a robotic arm, a pan and tilt mechanism as end-effector, and an actuation box that can rotate and around which the arm can wrap. The robot has a total of 15 degrees of freedom and, therefore, for the task of positioning the tool centre point in a bi-dimensional Cartesian space with a specific attitude, it has 10 degrees of redundancy. The robot is designed to operate in harsh environments and high temperatures and can deploy itself up to about 4.8 m. This paper presents the requirements that drove the design of the robot, the main aspects of the mechanical and electronic systems, the control strategy, and the results of preliminary experimental tests performed with a physical prototype to evaluate the robot performances

Task-Priority Control of Redundant Robotic Systems using Control Lyapunov and Control Barrier Function based Quadratic Programs

This paper presents a novel task-priority control framework for redundant robotic systems based on a hierarchy of control Lyapunov function (CLF) and control barrier function (CBF) based quadratic programs (QPs). The proposed method guarantees strict priority among different groups of tasks such as safety-related, operational and optimization tasks. Moreover, a soft priority measure in the form of penalty parameters can be employed to prioritize tasks at the same priority level. As opposed to kinematic control schemes, the proposed framework is a holistic approach to control of redundant robotic systems, which solves the redundancy resolution, dynamic control and control allocation problems simultaneously. Numerical simulations of a hyper-redundant articulated intervention autonomous underwater vehicle (AIAUV) is presented to validate the proposed framework.Comment: 21st IFAC World Congres

Stability Analysis for Set-based Control within the Singularity-robust Multiple Task-priority Inverse Kinematics Framework

Inverse kinematics algorithms are commonly used in robotic systems to accomplish desired behavior, and several methods exist to ensure the achievement of several tasks simultaneously. The multiple task-priority inverse kinematics framework allows tasks to be considered in a prioritized order by projecting task velocities through the nullspaces of higher priority tasks. This paper extends this framework to handle set-based tasks, i.e. tasks with a range of valid values, in addition to equality tasks, which have a specific desired value. Examples of such tasks are joint limit and obstacle avoidance. The proposed method is proven to ensure asymptotic convergence of the equality task errors and the satisfaction of all high-priority set-based tasks. Simulations results confirm the effectiveness of the proposed approach.(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control Retargetting Human Commands to Feasible Robot Control References

This article presents a robust and reliable human–robot collaboration (HRC) framework for bimanual manipulation. We propose an optimal motion adaptation method to retarget arbitrary human commands to feasible robot pose references while maintaining payload stability. The framework comprises three modules: 1) a task-space sequential equilibrium and inverse kinematics optimization ( task-space SEIKO ) for retargeting human commands and enforcing feasibility constraints, 2) an admittance controller to facilitate compliant human–robot physical interactions, and 3) a low-level controller improving stability during physical interactions. Experimental results show that the proposed framework successfully adapted infeasible and dangerous human commands into continuous motions within safe boundaries and achieved stable grasping and maneuvering of large and heavy objects on a real dual-arm robot via teleoperation and physical interaction. Furthermore, the framework demonstrated the capability in the assembly task of building blocks and the insertion task of industrial power connectors

Excitation and Stabilization of Passive Dynamics in Locomotion using Hierarchical Operational Space Control

This paper describes a hierarchical operational space control (OSC) method based on least square optimization and outlines different ways to reduce the dimensionality of the optimization vector. The framework allows to emulate various behaviors by prioritized task-space motion, joint torque, and contact force optimization. Moreover, a methodology is introduced to partially excite the natural dynamics of the robot by open-loop motor regulation while the entire behavior is stabilized by hierarchical OSC. As a major contribution, the presented control strategies are tested and validated in real hardware walking, trotting, and pronking experiments using a fully torque controllable quadrupedal robot

Vision-based assistance for wheelchair navigation along corridors

International audienceIn case of motor impairments, steering a wheelchair can become a hazardous task. Typically, along corridors, joystick jerks induced by uncontrolled motions are source of wall collisions. This paper describes a vision based assistance solution for safe indoor semi-autonomous navigation purposes. To this aim, the control process is based on a visual servoing process designed for wall avoidance purposes. As the patient manually drives the wheelchair, a virtual guide is defined to progressively activate an automatic trajectory cor- rection. The proposed solution does not require any knowledge of the environment. Experiments have been conducted over corridors that present different configurations and illumination conditions. Results demonstrate the ability of the system to smoothly and adaptively assist people during their motions

Control of a hybrid robotic system for computer-assisted interventions in dynamic environments

International audiencePurpose Minimally invasive surgery is becoming the standard treatment of care for a variety of procedures. Surgeons need to display a high level of proficiency to overcome the challenges imposed by the minimal access. Especially when operating on a dynamic organ, it becomes very difficult to align instruments reliably and precisely. In this paper, a hybrid ro-botic system and a dedicated robotic control approach are proposed to assist the surgeon performing complex surgical gestures in a dynamic environment. Methods The proposed hybrid robotic system consists of a rigid robot arm on top of which a continuum robot is mounted in series. The continuum robot is locally actuated with McKibben muscles. A control scheme is adopted based on quadratic programming framework. It is shown that this framework allows enforcing a set of constraints on the pose of the tip, as well as of the instrument shaft, which is commanded to slide in and out through the entry point. Results Through simulation and experiments it is shown how the robot tool-tip is able to follow sinus-oidal trajectories of 0.37 Hz and 2 Hz, corresponding to motion due to breathing and heartbeat respectively, while maintaining the instrument shaft pivoting nicely about the entry point. The positioning and tracking accuracy of such system is shown to lie below 3mm in position and 5 • in angle. Herbert De Praetere is with UZ Leuven, Cardiac surgery, Conclusion The results suggest a good potential for applying the proposed technology to assist the surgeon during complex robot-assisted interventions. It is also illustrated that even when using flexible hence relatively safe end-effectors, it is possible to reach acceptable tracking behaviour at relatively high frequencies

미지 환경에서의 안전 비행 운송을 위한 협업제어 및 경로생성 기법

학위논문 (박사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 김현진.Recently, aerial manipulators using unmanned aerial vehicles (UAVs) are receiving attention due to their superior mobility in three-dimensional space. It can be applied to a wide range of applications such as inspection of hard-to-reach structure or aerial transportation. This dissertation presents a viable approach to safe aerial transportation in unknown environments by using multiple aerial manipulators. Unlike existing approaches for cooperative manipulation based on force decomposition or impedance-based control that often requ- ire heavy or expensive force/torque sensors, this dissertation suggests a method without such sensors, by exploiting the decoupled dynamics to develop estimation and control alg- orithms. With the decoupled dynamics and the assumption of rigid grasp, an online estimator is designed initially to estimate the mass and inertial properties of an unknown payload using the states of the aerial manipulator only. Stable adaptive controller based on the online estimated parameter is then designed using Lyapunov methods. Through simulations, the performance of the proposed controller is compared with conventional passivity-based adaptive algorithms. This dissertation also proposes a motion generation algorithm for cooperative manipulators to transport a payload safely. If the payload is excessively heavy in comparison with the transportation ability of an aerial robot, an aerial robot may crash because of actuation limits on the motors. As a first step, the allowable flight envelope is analyzed with respect to the position of the end-effector. In order to keep the end-effector in the allowable fight region, kinematic coordination between a payload and cooperative aerial manipulators is first studied. A two-layer framework, in which the first layer computes the motion reference of the end-effectors and the second layer calculates the joint motion of the corresponding manipulator, is then developed in a task-prioritized fashion. When generating aerial manipulator trajectories, the desired trajectory is calculated to satisfy the unilateral constraints obtained by the allowable flight envelope. This work also considers the obstacle avoidance of cooperative aerial manipulators in unknown environments. Using the relative distance between an aerial robot and an obstacle as measured by an RGB-D camera and point cloud library (PCL), dynamic movement primitives (DMPs) modify the desired trajectory. By having the leader robot detect an obstacle and the follower robots maintain a given relative distance with the leader, improved efficiency of obstacle avoidance for cooperative robots can be achieved. Finally, the proposed synthesis of estimation, control, and planning algorithms are validated with experiments using custom-made aerial manipulators combined with a two-DOF (Degree Of Freedom) robotic arm. The proposed method is validated with trajectory tracking using two types of payloads. Cooperative aerial transportation in unknown environments is also performed with an unknown obstacle. Both experimental results suggest that the proposed approach can be utilized for safe cooperative aerial transportation.1 Introduction 1 1.1 Background and Motivations 1 1.2 Literature Survey 4 1.2.1 Cooperative Manipulation 4 1.2.2 Handling an Unknown Object 7 1.2.3 Obstacle Avoidance for Cooperative Robots 8 1.3 Research Objectives and Contributions 9 1.3.1 Estimation and Control Algorithm 10 1.3.2 Motion Planning within the Allowable Flight Envelope 11 1.3.3 Real-time Obstacle Avoidance using an RGB-D Camera 11 1.4 Thesis Organization 12 2 Background 14 2.1 Dynamics for Cooperative Aerial Manipulator 14 2.1.1 Rigid Body Statics 15 2.1.2 Dynamics for Single Aerial Manipulator 16 2.1.3 Decoupled Dynamics 19 2.2 Task Priority 22 2.3 DMPs 24 3 Estimator and Controller Design 26 3.1 Payload Mass and Inertia Parameter Estimation 28 3.1.1 System Parametrization 28 3.1.2 On-line Parameter Estimator 29 3.1.3 Robust Analysis for Measurement Noise 32 3.2 Controller Design 34 3.3 Simulation Results 40 4 Path Planning 45 4.1 Allowable Payload for Each Aerial Manipulator 45 4.2 Trajectory Generation with Unilateral Constraints 49 4.2.1 End-eector Trajectory Generation 49 4.2.2 Inverse Kinematics with Null Space Approach 49 4.2.3 Task Prioritization with Unilateral Constraints 56 5 Obstacle Avoidance in Unknown Environments 60 5.1 Obstacle Detection 60 5.2 Movement Primitives for Cooperative Aerial Manipulators 64 6 Experimental Validation and Results 71 6.1 Simulation Validation for Moving Obstacle 71 6.2 Experimental Setup 74 6.3 Experiment for Cooperative Aerial Transportation 77 6.3.1 Path Following with Two Types of Payloads 77 6.3.2 Aerial Transportations in Unknown Environments 78 7 Conclusions 93 Abstract (in Korean) 105Docto