95 research outputs found
Formation Flight in Dense Environments
Formation flight has a vast potential for aerial robot swarms in various
applications. However, existing methods lack the capability to achieve fully
autonomous large-scale formation flight in dense environments. To bridge the
gap, we present a complete formation flight system that effectively integrates
real-world constraints into aerial formation navigation. This paper proposes a
differentiable graph-based metric to quantify the overall similarity error
between formations. This metric is invariant to rotation, translation, and
scaling, providing more freedom for formation coordination. We design a
distributed trajectory optimization framework that considers formation
similarity, obstacle avoidance, and dynamic feasibility. The optimization is
decoupled to make large-scale formation flights computationally feasible. To
improve the elasticity of formation navigation in highly constrained scenes, we
present a swarm reorganization method which adaptively adjusts the formation
parameters and task assignments by generating local navigation goals. A novel
swarm agreement strategy called global-remap-local-replan and a formation-level
path planner is proposed in this work to coordinate the swarm global planning
and local trajectory optimizations efficiently. To validate the proposed
method, we design comprehensive benchmarks and simulations with other
cutting-edge works in terms of adaptability, predictability, elasticity,
resilience, and efficiency. Finally, integrated with palm-sized swarm platforms
with onboard computers and sensors, the proposed method demonstrates its
efficiency and robustness by achieving the largest scale formation flight in
dense outdoor environments.Comment: Submitted for IEEE Transactions on Robotic
Quadrotor team modeling and control for DLO transportation
94 p.Esta Tesis realiza una propuesta de un modelado dinámico para el transporte de sólidos lineales deformables (SLD) mediante un equipo de cuadricópteros. En este modelo intervienen tres factores: - Modelado dinámico del sólido lineal a transportar. - Modelo dinámico del cuadricóptero para que tenga en cuenta la dinámica pasiva y los efectos del SLD. - Estrategia de control para un transporte e ciente y robusto. Diferenciamos dos tareas principales: (a) lograr una con guración cuasiestacionaria de una distribución de carga equivalente a transportar entre todos los robots. (b) Ejecutar el transporte en un plano horizontal de todo el sistema. El transporte se realiza mediante una con guración de seguir al líder en columna, pero los cuadricópteros individualmente tienen que ser su cientemente robustos para afrontar todas las no-linealidades provocadas por la dinámica del SLD y perturbaciones externas, como el viento. Los controladores del cuadricóptero se han diseñado para asegurar la estabilidad del sistema y una rápida convergencia del sistema. Se han comparado y testeado estrategias de control en tiempo real y no-real para comprobar la bondad y capacidad de ajuste a las condiciones dinámicas cambiantes del sistema. También se ha estudiado la escalabilidad del sistema
Optimal Control of Multiple Quadrotors for Transporting a Cable Suspended Payload
In this thesis, the main aim is to improve the flight control performance for a cable suspended payload with single and two quadrotors based on optimised control techniques. The study utilised optimal controllers, such as the Linear Quadratic Regulator LQR, the Iterative based LQR (ILQR), the Model Predictive Control MPC and the dynamic game controller to solve tracking control problems in terms of stabilisation, accuracy, constraints and collision avoidance. The LQR control was applied to the system as the first control method and compared with the classical Proportional-Derivative controller PD. It was used to achieve the load
path tracking performance for single and two quadrotors with a cable slung load.
The second controller was ILQR, which was developed based on the LQR control method to deal with the model nonlinearity. The MPC technique was also applied to the linearised nonlinear model LMPC of two quadrotors with a payload suspended by cables and compared with a nonlinear MPC (NMPC). Both MPC controllers LMPC and NMPC considered the constraints imposed on the system states and control inputs. The dynamic game control method was developed based
on an incentive strategy for a leader-follower framework with the consideration of different optimal cost functions. It was applied to the linearised nonlinear model.
Selecting these control techniques led to a number of achievements. Firstly, they improved the system performance in terms of achieving the system stability and reducing the steady-state errors. Secondly, the system parameter uncertainties were taken into consideration by utilising the ILQR controller. Thirdly, the MPC controllers guaranteed the handling of constraints and external disturbances in linear and nonlinear systems. Finally, avoiding collision between the leader and follower robots was achieved by applying the dynamic game controller. The controllers were
tested in MATLAB simulation and verified for various desired predefined trajectories.
In real experiments, these controllers were used as high-level controllers, which produce the optimised trajectory points. Then a low-level controller (PD controller) was used to follow the optimised trajectory points
Virtual differential passivity based control of mechanical systems in the port-Hamiltonian framework
- …