Autonomous Robots for Active Removal of Orbital Debris

This paper presents a vision guidance and control method for autonomous robotic capture and stabilization of orbital objects in a time-critical manner. The method takes into account various operational and physical constraints, including ensuring a smooth capture, handling line-of-sight (LOS) obstructions of the target, and staying within the acceleration, force, and torque limits of the robot. Our approach involves the development of an optimal control framework for an eye-to-hand visual servoing method, which integrates two sequential sub-maneuvers: a pre-capturing maneuver and a post-capturing maneuver, aimed at achieving the shortest possible capture time. Integrating both control strategies enables a seamless transition between them, allowing for real-time switching to the appropriate control system. Moreover, both controllers are adaptively tuned through vision feedback to account for the unknown dynamics of the target. The integrated estimation and control architecture also facilitates fault detection and recovery of the visual feedback in situations where the feedback is temporarily obstructed. The experimental results demonstrate the successful execution of pre- and post-capturing operations on a tumbling and drifting target, despite multiple operational constraints

Infrared based monocular relative navigation for active debris removal

In space, visual based relative navigation systems suffer from the harsh illumination conditions of the target (e.g. eclipse conditions, solar glare, etc.). In current Rendezvous and Docking (RvD) missions, most of these issues are addressed by advanced mission planning techniques (e.g strict manoeuvre timings). However, such planning would not always be feasible for Active Debris Removal (ADR) missions which have more unknowns. Fortunately, thermal infrared technology can operate under any lighting conditions and therefore has the potential to be exploited in the ADR scenario. In this context, this study investigates the benefits and the challenges of infrared based relative navigation. The infrared environment of ADR is very much different to that of terrestrial applications. This study proposes a methodology of modelling this environment in a computationally cost effective way to create a simulation environment in which the navigation solution can be tested. Through an intelligent classification of possible target surface coatings, the study is generalised to simulate the thermal environment of space debris in different orbit profiles. Through modelling various scenarios, the study also discusses the possible challenges of the infrared technology. In laboratory conditions, providing the thermal-vacuum environment of ADR, these theoretical findings were replicated. By use of this novel space debris set-up, the study investigates the behaviour of infrared cues extracted by different techniques and identifies the issue of short-lifespan features in the ADR scenarios. Based on these findings, the study suggests two different relative navigation methods based on the degree of target cooperativeness: partially cooperative targets, and uncooperative targets. Both algorithms provide the navigation solution with respect to an online reconstruction of the target. The method for partially cooperative targets provides a solution for smooth trajectories by exploiting the subsequent image tracks of features extracted from the first frame. The second algorithm is for uncooperative targets and exploits the target motion (e.g. tumbling) by formulating the problem in terms of a static target and a moving map (i.e. target structure) within a filtering framework. The optical flow information is related to the target motion derivatives and the target structure. A novel technique that uses the quality of the infrared cues to improve the algorithm performance is introduced. The problem of short measurement duration due to target tumbling motion is addressed by an innovative smart initialisation procedure. Both navigation solutions were tested in a number of different scenarios by using computer simulations and a specific laboratory set-up with real infrared camera. It is shown that these methods can perform well as the infrared-based navigation solutions using monocular cameras where knowledge relating to the infrared appearance of the target is limited

Comprehensive simulation of cooperative robotic system for advanced composite manufacturing: A case study

Composite materials are widely used because of their light weight and high strength properties. They are typically made up of multi-directional layers of high strength fibres, connected by a resin. The manufacturing of composite parts is complex, time-consuming and prone to errors. This work investigates the use of robotics in the field of composite material manufacturing, which has not been well investigated to date (particularly in simulation). Effective autonomous material transportation, accurate localization and limited material deformation during robotic grasping are required for optimum placement and lay-up. In this paper, a simulation of a proposed cooperative robotic system, which integrates an autonomous mobile robot with a fixed-base manipulator, is presented. An approach based on machine vision is adopted to accurately track the position and orientation of the fibre plies. A simulation platform with a built-in physics engine is used to simulate material deformation under gravity and external forces. This allows realistic simulation of robotic manipulation for raw materials. The results demonstrate promising features of the proposed system. A root mean square error of 9.00 mm for the estimation of the raw material position and 0.05 degrees for the fibre orientation detection encourages further research for developing the proposed robotic manufacturing system

Relative Navigation Strategy About Unknown and Uncooperative Targets

In recent years, space debris has become a threat for satellites operating in low Earth orbit. Even by applying mitigation guidelines, their number will still increase over the course of the century. As a consequence, active debris removal missions and on-orbit servicing missions have gained momentum at both academic and industrial level. The crucial step in both scenarios is the capability of navigating in the neighborhood of a target resident space object. This problem has been tackled many times in literature with varying level of cooperativeness of the target required. While several techniques are available when the target is cooperative or its shape is known, no approach is mature enough to deal with uncooperative and unknown targets. This paper proposes a hybrid method to tackle this issue called Coarse Model-Based Relative Navigation (CoMBiNa). The main idea of this algorithm is to split the mission into two phases. During the first phase, the algorithm constructs a coarse model of the target. In the second phase, this coarse model is used as a reference for a relative navigation technique, effectively shifting the focus toward state and inertia estimation. In addition, this paper proposes a strategy to leverage the structure of the selected navigation method to detect and reject outliers. To conclude, CoMBiNa is tested on a simulated environment to highlight its benefits and its shortcomings, while also assessing its applicability on a limited-resource single-board computer

Fault-tolerant feature-based estimation of space debris motion and inertial properties

The exponential increase of the needs of people in the modern society and the contextual development of the space technologies have led to a significant use of the lower Earth’s orbits for placing artificial satellites. The current overpopulation of these orbits also increased the interest of the major space agencies in technologies for the removal of at least the biggest spacecraft that have reached their end-life or have failed their mission. One of the key functionalities required in a mission for removing a non-cooperative spacecraft is the assessment of its kinematics and inertial properties. In a few cases, this information can be approximated by ground observations. However, a re-assessment after the rendezvous phase is of critical importance for refining the capture strategies preventing accidents. The CADET program (CApture and DE-orbiting Technologies), funded by Regione Piemonte and led by Aviospace s.r.l., involved Politecnico di Torino in the research for solutions to the above issue. This dissertation proposes methods and algorithms for estimating the location of the center of mass, the angular rate, and the moments of inertia of a passive object. These methods require that the chaser spacecraft be capable of tracking several features of the target through passive vision sensors. Because of harsh lighting conditions in the space environment, feature-based methods should tolerate temporary failures in detecting features. The principal works on this topic do not consider this important aspect, making it a characteristic trait of the proposed methods. Compared to typical v treatments of the estimation problem, the proposed techniques do not depend solely on state observers. However, methods for recovering missing information, like compressive sampling techniques, are used for preprocessing input data to support the efficient usage of state observers. Simulation results showed accuracy properties that are comparable to those of the best-known methods already proposed in the literature. The developed algorithms were tested in the laboratory staged by Aviospace s.r.l., whose name is CADETLab. The results of the experimental tests suggested the practical applicability of such algorithms for supporting a real active removal mission

Spacecraft Position and Attitude Formation Control using Line-of-Sight Observations

This paper studies formation control of an arbitrary number of spacecraft based on a serial network structure. The leader controls its absolute position and absolute attitude with respect to an inertial frame, and the followers control its relative position and attitude with respect to another spacecraft assigned by the serial network. The unique feature is that both the absolute attitude and the relative attitude control systems are developed directly in terms of the line-of-sight observations between spacecraft, without need for estimating the full absolute and relative attitudes, to improve accuracy and efficiency. Control systems are developed on the nonlinear configuration manifold, guaranteeing exponential stability. Numerical examples are presented to illustrate the desirable properties of the proposed control system

Dynamic Control of Mobile Multirobot Systems: The Cluster Space Formulation

The formation control technique called cluster space control promotes simplified specification and monitoring of the motion of mobile multirobot systems of limited size. Previous paper has established the conceptual foundation of this approach and has experimentally verified and validated its use for various systems implementing kinematic controllers. In this paper, we briefly review the definition of the cluster space framework and introduce a new cluster space dynamic model. This model represents the dynamics of the formation as a whole as a function of the dynamics of the member robots. Given this model, generalized cluster space forces can be applied to the formation, and a Jacobian transpose controller can be implemented to transform cluster space compensation forces into robot-level forces to be applied to the robots in the formation. Then, a nonlinear model-based partition controller is proposed. This controller cancels out the formation dynamics and effectively decouples the cluster space variables. Computer simulations and experimental results using three autonomous surface vessels and four land rovers show the effectiveness of the approach. Finally, sensitivity to errors in the estimation of cluster model parameters is analyzed.Fil: Mas, Ignacio Agustin. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kitts, Christopher. Santa Clara University; Estados Unido

GRASP News Volume 9, Number 1

A report of the General Robotics and Active Sensory Perception (GRASP) Laboratory