Repeated Impact-Based Capture of a Spinning Object by a Dual-Arm Space Robot

This paper presents detumbling and capture of space debris by a dual-arm space robot for active space debris removal missions. Space debris, such as a malfunctioning satellite or a rocket upper stage, often has uncontrolled tumbling motion. It also has uncertainties in its parameters, such as inertial characteristics or surface frictional roughness. These factors make the debris capture missions difficult to accomplish. To cope with such challenging missions, we propose a detumbling and capture control method for a dual-arm robot based on repeated impact capable of suppressing the debris motion by repeatedly utilizing an effect of a passive damping factor in the contact characteristics. In this paper, as the initial step of a study on the repeated impact-based capture method, we assume that the capture target is a rocket upper stage that can be simply modeled as a cylindrical body and mainly has angular velocity motion in its principle axis of inertia. A motion tracking control law of an end-effector of the robot arm is introduced to maintain the repeated impact. The proposed control method enables the robot to accomplish the detumbling and capture without precise estimation of the inertial characteristics and surface frictional roughness of the debris. The validity of the proposed method is presented by numerical simulations and planar microgravity experiments using an air-floating system. In particular, the experimental evaluation shows the fundamental feasibility of the proposed method, and thus, the result contributes to a practical application

Cooperative Transportation of an Object based on Fractional Order Controllers

Advanced control techniques have been used in simulations to overcome nonlinear phenomena in order to describe the performance of robots with two rotational (RR) degrees-of-freedom (dof). Given the current state-of-the-art, fractional order algorithms lead to better performance when compared to integer order controllers. Also, the development of simulation platforms allows evaluating the best control methodology. In this context, the use of RR robots attached to mobile platforms, denoted in this paper as RR mobile robots, demonstrates a remarkable ability in manipulating and transporting objects. The present work aims to study two cooperative RR mobile robots by analyzing the manipulator’s trajectory and the forces applied to the common load. Are considered two robotic platforms based on an 8-bit microcontroller with inverse kinematics based on the Denavit-Hartenberg formulation and fractional order PID controllers inspired in the Grünwald-Letnikov definition.N/

Offline and Online Planning and Control Strategies for the Multi-Contact and Biped Locomotion of Humanoid Robots

In the past decades, the Research on humanoid robots made progress forward accomplishing exceptionally dynamic and agile motions. Starting from the DARPA Robotic Challenge in 2015, humanoid platforms have been successfully employed to perform more and more challenging tasks with the eventual aim of assisting or replacing humans in hazardous and stressful working situations. However, the deployment of these complex machines in realistic domestic and working environments still represents a high-level challenge for robotics. Such environments are characterized by unstructured and cluttered settings with continuously varying conditions due to the dynamic presence of humans and other mobile entities, which cannot only compromise the operation of the robotic system but can also pose severe risks both to the people and the robot itself due to unexpected interactions and impacts. The ability to react to these unexpected interactions is therefore a paramount requirement for enabling the robot to adapt its behavior to the task needs and the characteristics of the environment. Further, the capability to move in a complex and varying environment is an essential skill for a humanoid robot for the execution of any task. Indeed, human instructions may often require the robot to move and reach a desired location, e.g., for bringing an object or for inspecting a specific place of an infrastructure. In this context, a flexible and autonomous walking behavior is an essential skill, study of which represents one of the main topics of this Thesis, considering disturbances and unfeasibilities coming both from the environment and dynamic obstacles that populate realistic scenarios.  Locomotion planning strategies are still an open theme in the humanoids and legged robots research and can be classified in sample-based and optimization-based planning algorithms. The first, explore the configuration space, finding a feasible path between the start and goal robot’s configuration with different logic depending on the algorithm. They suffer of a high computational cost that often makes difficult, if not impossible, their online implementations but, compared to their counterparts, they do not need any environment or robot simplification to find a solution and they are probabilistic complete, meaning that a feasible solution can be certainly found if at least one exists. The goal of this thesis is to merge the two algorithms in a coupled offline-online planning framework to generate an offline global trajectory with a sample-based approach to cope with any kind of cluttered and complex environment, and online locally refine it during the execution, using a faster optimization-based algorithm that more suits an online implementation. The offline planner performances are improved by planning in the robot contact space instead of the whole-body robot configuration space, requiring an algorithm that maps the two state spaces.   The framework proposes a methodology to generate whole-body trajectories for the motion of humanoid and legged robots in realistic and dynamically changing environments.  This thesis focuses on the design and test of each component of this planning framework, whose validation is carried out on the real robotic platforms CENTAURO and COMAN+ in various loco-manipulation tasks scenarios. &nbsp

Planning and Control Strategies for Motion and Interaction of the Humanoid Robot COMAN+

Despite the majority of robotic platforms are still confined in controlled environments such as factories, thanks to the ever-increasing level of autonomy and the progress on human-robot interaction, robots are starting to be employed for different operations, expanding their focus from uniquely industrial to more diversified scenarios. Humanoid research seeks to obtain the versatility and dexterity of robots capable of mimicking human motion in any environment. With the aim of operating side-to-side with humans, they should be able to carry out complex tasks without posing a threat during operations. In this regard, locomotion, physical interaction with the environment and safety are three essential skills to develop for a biped. Concerning the higher behavioural level of a humanoid, this thesis addresses both ad-hoc movements generated for specific physical interaction tasks and cyclic movements for locomotion. While belonging to the same category and sharing some of the theoretical obstacles, these actions require different approaches: a general high-level task is composed of specific movements that depend on the environment and the nature of the task itself, while regular locomotion involves the generation of periodic trajectories of the limbs. Separate planning and control architectures targeting these aspects of biped motion are designed and developed both from a theoretical and a practical standpoint, demonstrating their efficacy on the new humanoid robot COMAN+, built at Istituto Italiano di Tecnologia. The problem of interaction has been tackled by mimicking the intrinsic elasticity of human muscles, integrating active compliant controllers. However, while state-of-the-art robots may be endowed with compliant architectures, not many can withstand potential system failures that could compromise the safety of a human interacting with the robot. This thesis proposes an implementation of such low-level controller that guarantees a fail-safe behaviour, removing the threat that a humanoid robot could pose if a system failure occurred

Simultaneous Capture and Detumble of a Resident Space Object by a Free-Flying Spacecraft-Manipulator System

The article of record as published may be found at https://doi.org/10.3389/frobt.2019.00014A maneuver to capture and detumble an orbiting space object using a chaser spacecraft equipped with a robotic manipulator is presented. In the proposed maneuver, the capture and detumble objectives are integrated into a unified set of terminal constraints. Terminal constraints on the end-effector’s position and velocity ensure a successful capture, and a terminal constraint on the chaser’s momenta ensures a post-capture chaser-target system with zero angular momentum. The manipulator motion required to achieve a smooth, impact-free grasp is gradually stopped after capture, equalizing the momenta across all bodies, rigidly connecting the two vehicles, and completing the detumble of the newly formed chaser-target system without further actuation. To guide this maneuver, an optimization-based approach that enforces the capture and detumble terminal constraints, avoids collisions, and satisfies actuation limits is used. The solution to the guidance problem is obtained by solving a collection of convex programming problems, making the proposed guidance approach suitable for onboard implementation and real-time use. This simultaneous capture and detumble maneuver is evaluated through numerical simulations and hardware-in-the-loop experiments. Videos of the numerically simulated and experimentally demonstrated maneuvers are included as Supplementary Material