Bipedal Hopping: Reduced-order Model Embedding via Optimization-based Control

This paper presents the design and validation of controlling hopping on the 3D bipedal robot Cassie. A spring-mass model is identified from the kinematics and compliance of the robot. The spring stiffness and damping are encapsulated by the leg length, thus actuating the leg length can create and control hopping behaviors. Trajectory optimization via direct collocation is performed on the spring-mass model to plan jumping and landing motions. The leg length trajectories are utilized as desired outputs to synthesize a control Lyapunov function based quadratic program (CLF-QP). Centroidal angular momentum, taking as an addition output in the CLF-QP, is also stabilized in the jumping phase to prevent whole body rotation in the underactuated flight phase. The solution to the CLF-QP is a nonlinear feedback control law that achieves dynamic jumping behaviors on bipedal robots with compliance. The framework presented in this paper is verified experimentally on the bipedal robot Cassie.Comment: 8 pages, 7 figures, accepted by IROS 201

Rajaplaneerimine multi-robot süsteemile jagatud lasti transportimisel

Shared payload transportation has emerged as one of the key real-world applications that warrants the deployment of multiple robots. The key motivation stems from the fact that actuation and sensing abilities of multiple robots can be pooled together to transport objects that are either too big or heavy to be handled by a single robot. This thesis proposes algorithmic and software frameworks to achieve precise multi-robot coordination for object transportation. On the algorithmic side, a trajectory optimization formulation is developed which generates collision-free and smooth trajectories for the robots transporting the object. State-of-the art Gradient Descent variants are utilized for obtaining the solution. On the software side, a trajectory planner (local planner) is developed and integrated to Robot Operating System (ROS). The local planner is responsible for calculating individual velocities for any number of robots forming a rigid geometric in-plane constellation. Extensive simulation as well as real-world experiments are performed to demonstrate the validity of the developed solutions. It is demonstrated that how the proposed trajectory optimization approach outperforms off-the-shelf planners with respect to metrics like smoothness and collision avoidance. In estonian: Ühise lasti transportimine mitme roboti poolt on kujunenud üheks rakendusvaldkonnaks, kus mitme roboti samaaegne kasutamine on õigustatud. Mitme roboti andureid ja ajameid on eriti kasulik kasutada transportimaks objekte, mis on ühe roboti jaoks kas liiga suured ja/või rasked. Käesolev lõputöö pakub välja algoritmilise ja tarkvaralise raamistiku, mis võimaldab täpselt koordineerida mitme roboti koostööd ühise lasti liigutamisel. Välja on töötatud trajektooride optimeerimise algoritm, mis genereerib kokkupõrkevabad ja sujuvad ühist objekti kandvate robotite trajektoorid. Selleks on kasutatud nüüdisaegset gradientlaskumise (ingl Gradient Descent) meetodit. Tarkvara poolelt on loodud trajektoori planeerija (lokaalne planeerija) ja see on integreeritud arendusplatvormil ROS (Robot Operating System). Lokaalne planeerija arvutab individuaalsed kiirused igale robotile, mis moodustavad ühise jäiga tasapinnalise kujundi, kusjuures robotite arv kujundis ei ole piiratud. Väljatöötatud lahenduse toimimist on kontrollitud ulatuslike simulatsioonide abil aga ka viies läbi praktilisi katseid. Väljapakutud trajektoori optimeerimise lahendus ületab olemasolevaid planeerijaidd nii trajektoori sujuvuse kui ka kokkupõrgete vältimise võime osas

On sensor fusion for airborne wind energy systems

A study on filtering aspects of airborne wind energy generators is presented. This class of renewable energy systems aims to convert the aerodynamic forces generated by tethered wings, flying in closed paths transverse to the wind flow, into electricity. The accurate reconstruction of the wing's position, velocity and heading is of fundamental importance for the automatic control of these kinds of systems. The difficulty of the estimation problem arises from the nonlinear dynamics, wide speed range, large accelerations and fast changes of direction that the wing experiences during operation. It is shown that the overall nonlinear system has a specific structure allowing its partitioning into sub-systems, hence leading to a series of simpler filtering problems. Different sensor setups are then considered, and the related sensor fusion algorithms are presented. The results of experimental tests carried out with a small-scale prototype and wings of different sizes are discussed. The designed filtering algorithms rely purely on kinematic laws, hence they are independent from features like wing area, aerodynamic efficiency, mass, etc. Therefore, the presented results are representative also of systems with larger size and different wing design, different number of tethers and/or rigid wings.Comment: This manuscript is a preprint of a paper accepted for publication on the IEEE Transactions on Control Systems Technology and is subject to IEEE Copyright. The copy of record is available at IEEEXplore library: http://ieeexplore.ieee.org

Flat systems, equivalence and trajectory generation

Flat systems, an important subclass of nonlinear control systems introduced via differential-algebraic methods, are defined in a differential geometric framework. We utilize the infinite dimensional geometry developed by Vinogradov and coworkers: a control system is a diffiety, or more precisely, an ordinary diffiety, i.e. a smooth infinite-dimensional manifold equipped with a privileged vector field. After recalling the definition of a Lie-Backlund mapping, we say that two systems are equivalent if they are related by a Lie-Backlund isomorphism. Flat systems are those systems which are equivalent to a controllable linear one. The interest of such an abstract setting relies mainly on the fact that the above system equivalence is interpreted in terms of endogenous dynamic feedback. The presentation is as elementary as possible and illustrated by the VTOL aircraft

Autonomous In-Orbit Satellite Assembly from a Modular Heterogeneous Swarm

This paper presents a decentralized, distributed guidance and control scheme to combine a heterogeneous swarm of component satellites into a large satellite structure. The component satellites for the heterogeneous swarm are chosen to promote flexibility in final shape inspired by crystal structures and Islamic tile art. After the ideal fundamental building blocks are selected, basic nanosatellite-class satellite designs are made to assist in simulations involving attitude control. The Swarm Orbital Construction Algorithm (SOCA) is a guidance and control algorithm to allow for the limited type heterogeneity and docking ability required for in-orbit assembly. The algorithm consists of two parts, a distributed auction which uses barrier functions to ensure the proper agent selection for each target, and a trajectory generation portion which leverages model predictive control and sequential convex programming to achieve optimal collision-free trajectories to the desired target point even with nonlinear system dynamics. The optimization constraints use a boundary layer to determine whether the collision avoidance or the docking constraints should be applied. The algorithm was tested in a simulated perturbed 6-DOF spacecraft dynamic environment for planar and out-of-plane final structures and on two robotic platforms, including a swarm of frictionless spacecraft simulation robots