[ { "id": "authors:nn5qr-hqx07", "collection": "authors", "collection_id": "nn5qr-hqx07", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20190722-095828499", "type": "conference_item", "title": "Distributed multi-target relative pose estimation for cooperative spacecraft swarm", "author": [ { "family_name": "Matsuka", "given_name": "Kai", "orcid": "0000-0003-2116-9756", "clpid": "Matsuka-Kai" }, { "family_name": "Lupu", "given_name": "Elena Sorina", "orcid": "0000-0002-3968-2630", "clpid": "Lupu-E-S" }, { "family_name": "Nakka", "given_name": "Yashwanth Kumar", "orcid": "0000-0001-7897-3644", "clpid": "Nakka-Yashwanth-K" }, { "family_name": "Foust", "given_name": "Rebecca", "orcid": "0000-0003-1470-1716", "clpid": "Foust-Rebecca" }, { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Had\u00e6gh", "given_name": "Fred", "clpid": "Hadaegh-F-Y" } ], "abstract": "Multi-agent relative state estimation is critical in enabling full swarm autonomy. However, relative pose estimation of hundreds to thousands of cooperative agents is challenging due to limited sensing, limited communication, and scalability. We present a distributed algorithm for cooperative multi-agent localization with both limited relative sensing and communication. Each agent locally exchanges the relative measurements and jointly estimates the relative poses of its local neighbors. Because the algorithm only estimates the local neighbors, the number of states does not grow with the total number of agents given the same local sensing and communication graphs, making the algorithm suitable for swarm application. The proposed algorithm is applied to spacecraft swarm localization and verified in simulation and experiments. Experiments are conducted on Caltech's robotic spacecraft simulators, the Multi-Spacecraft Testbed for Autonomy Research (M-STAR), where each spacecraft uses vision-based relative measurements.", "publisher": "Caltech Library", "publication_date": "2019-07-22" }, { "id": "authors:rcrtq-ztb53", "collection": "authors", "collection_id": "rcrtq-ztb53", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20190109-132944040", "type": "conference_item", "title": "Solving Optimal Control with Nonlinear Dynamics Using Sequential Convex Programming", "book_title": "AIAA Scitech 2019 Forum", "author": [ { "family_name": "Foust", "given_name": "Rebecca", "orcid": "0000-0003-1470-1716", "clpid": "Foust-Rebecca" }, { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Hadaegh", "given_name": "Fred Y.", "clpid": "Hadaegh-F-Y" } ], "abstract": "Sequential convex programming (SCP) is a useful tool in obtaining real-time solutions to direct optimal control, but it is unable to adequately model nonlinear dynamics due to the linearization and discretization required. As nonlinear program solvers are not yet functioning\nin real-time, a tool is needed to bridge the gap between satisfying the nonlinear dynamics and completing execution fast enough to be useful. This paper presents a real-time control algorithm, sequential convex programming with nonlinear dynamics correction (SCPn), which ameliorates the performance of SCP under nonlinear dynamics. Simulations are presented to validate the efficacy of the method.", "doi": "10.2514/6.2019-0652", "isbn": "978-1-62410-578-4", "publication_date": "2019-01", "pages": "1-15" }, { "id": "authors:97hth-tde87", "collection": "authors", "collection_id": "97hth-tde87", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20181010-123842437", "type": "conference_item", "title": "Ultra-Soft Electromagnetic Docking with Applications to In-Orbit Assembly", "author": [ { "family_name": "Foust", "given_name": "Rebecca C.", "orcid": "0000-0003-1470-1716", "clpid": "Foust-Rebecca" }, { "family_name": "Lupu", "given_name": "Elena Sorina", "orcid": "0000-0002-3968-2630", "clpid": "Lupu-E-S" }, { "family_name": "Nakka", "given_name": "Yashwanth Kumar", "orcid": "0000-0001-7897-3644", "clpid": "Nakka-Yashwanth-K" }, { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Hadaegh", "given_name": "Fred Y.", "clpid": "Hadaegh-F-Y" } ], "abstract": "Docking small satellites in space is a high-risk operation due to the uncertainty in relative position and orientation and the lack of mature docking technologies. This is particularly true for missions that involve multiple docking and undocking procedures like swarm-based construction and reconfiguration. In this paper, an electromagnetic docking system is proposed to mitigate these risks through robust, ultra-soft, propellant-free docking. Designed with reconfigurable self-assembly in mind, the gripping mechanism is androgynous, able to dock at a variety of relative orientations, and tolerant of small misalignments. The mechanical and control design of the system is presented and tested in both simulation and on a fleet of 6 degree-of-freedom (DOF) spacecraft simulators. The spacecraft simulators oat on the precision flat floor facility in the Caltech Aerospace Robotics and Control lab, the largest of its kind at any university. The performance of the electromagnetic docking system on-board the simulators is then compared against a propulsive docking system.", "publisher": "International Astronautical Federation", "publication_date": "2018-10" }, { "id": "authors:fe3er-haq75", "collection": "authors", "collection_id": "fe3er-haq75", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20180706-160821260", "type": "conference_item", "title": "Distributed Control Of An Evolving Satellite Assembly During In-Orbit Construction", "author": [ { "family_name": "Foust", "given_name": "Rebecca C.", "orcid": "0000-0003-1470-1716", "clpid": "Foust-Rebecca" }, { "family_name": "Zhao", "given_name": "Michelle", "clpid": "Zhao-Michelle" }, { "family_name": "Oliver", "given_name": "Suzanne", "clpid": "Oliver-Suzanne" }, { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Hadaegh", "given_name": "Fred Y.", "clpid": "Hadaegh-F-Y" } ], "abstract": "This paper presents a method for controlling sets of docked satellites during in-orbit construction of a large-scale satellite assembly from a swarm of heterogeneous satellites. Such a system can be used to enable missions from sparse aperture telescopes to elaborate space stations. Once two or more agents from the swarm are docked, the resulting assembly is an over-actuated system so position and attitude controllers must determine which of the available actuators to use. Typically, control allocation for over-actuated systems is done using a simple linear program, but for this scheme the mass properties and number of control points changes. As a result, the linear program solved changes with each new agent that docks with the assembly so the agents must know how to alter the linear program for additional agents and remove control points whose plumes would interact with those agents. In most systems, this linear program is solved by a central computer, but for this system the actuators belong to distinct agents so to increase reliability, each agent solves the same linear program and executes its portion of the resulting control command. This paper sets up the general linear program that each agent in the assembly must solve and then establishes the rules for altering that program when new agents dock. Initial simulations allow the agents to dock as they come into proximity along their respective trajectories to their target locations. This can lead to instability and uncontrollability if the agents dock in certain configurations, so the control allocation rules are extended to prevent uncontrollable or unstable docking scenarios. The logic used for this is based on the moment of inertia and the available actuation ability. Simulations in 6DOF perturbed satellite dynamics show the efficacy of this approach in preventing uncontrollable assemblies and bringing the assemblies together into the desired final configuration.", "publisher": "Caltech Library", "publication_date": "2018-07-06" }, { "id": "authors:3kd0e-b9j39", "collection": "authors", "collection_id": "3kd0e-b9j39", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20161206-152153163", "type": "conference_item", "title": "Real-Time Optimal Control and Target Assignment for Autonomous In-Orbit Satellite Assembly from a Modular Heterogeneous Swarm", "author": [ { "family_name": "Foust", "given_name": "Rebecca", "orcid": "0000-0003-1470-1716", "clpid": "Foust-Rebecca" }, { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Hadaegh", "given_name": "Fred Y.", "clpid": "Hadaegh-F-Y" } ], "abstract": "This paper presents a decentralized optimal guidance and control scheme to combine a heterogeneous swarm of component satellites, rods and connectors, into a large satellite structure. By expanding prior work on a decentralized auction algorithm with model predictive control using sequential convex programming (MPC-SCP) to allow for the limited type heterogeneity and docking ability required for in-orbit assembly. The assignment is performed using a distributed auction with a variable number of targets and strict bonding rules to address the heterogeneity. MPC-SCP is used to generate the collision-free trajectories, with modifications to the constraints to allow docking.", "publisher": "American Astronomical Society AAS", "publication_date": "2016-02-18" }, { "id": "authors:p3ve6-c4j28", "collection": "authors", "collection_id": "p3ve6-c4j28", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170214-131856997", "type": "conference_item", "title": "Feedback-Based Inhomogeneous Markov Chain Approach To Probabilistic Swarm Guidance", "author": [ { "family_name": "Bandyopadhyay", "given_name": "Saptarshi", "clpid": "Bandyopadhyay-S" }, { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Hadaegh", "given_name": "Fred Y.", "clpid": "Hadaegh-F-Y" } ], "abstract": "This paper presents a novel and generic distributed swarm guidance algorithm using inhomogeneous\nMarkov chains that guarantees superior performance over existing homogeneous\nMarkov chain based algorithms, when the feedback of the current swarm distribution is available.\nThe probabilistic swarm guidance using inhomogeneous Markov chain (PSG\u2013IMC)\nalgorithm guarantees sharper and faster convergence to the desired formation or unknown\ntarget distribution, minimizes the number of transitions for achieving and maintaining the\nformation even if the swarm is damaged or agents are added/removed from the swarm, and\nensures that the agents settle down after the swarm's objective is achieved. This PSG\u2013IMC\nalgorithm relies on a novel technique for constructing Markov matrices for a given stationary\ndistribution. This technique incorporates the feedback of the current swarm distribution,\nminimizes the coefficient of ergodicity and the resulting Markov matrix satisfies motion constraints.\nThis approach is validated using Monte Carlo simulations of the PSG\u2013IMC algorithm\nfor pattern formation and goal searching applications", "publisher": "Caltech Library", "publication_date": "2015-06-08" }, { "id": "authors:ydqek-6sr82", "collection": "authors", "collection_id": "ydqek-6sr82", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170214-120751873", "type": "conference_item", "title": "Swarms of Femtosats for Synthetic Aperture Applications", "author": [ { "family_name": "Chung", "given_name": "Soon-Jo", "orcid": "0000-0002-6657-3907", "clpid": "Chung-Soon-Jo" }, { "family_name": "Hadaegh", "given_name": "F. Y.", "clpid": "Hadaegh-F-Y" } ], "abstract": "The Silicon Wafer Integrated Femtosatellites (SWIFT) Swarm Project presents a new paradigm-shifting definition of spacecraft technology that can enable flight of swarms of fully capable femtosats. One of the most important applications of SWIFT is a distributed aperture array. \nNew swarm Golay array configurations are introduced and shown to dramatically increase the effective diameter derived from optical performance metrics. A system cost analysis based on this comparison justifies deploying a large number of spacecraft for sparse aperture applications.", "publisher": "Caltech Library", "publication_date": "2011-05-18" } ]