Real-Time Planning with Multi-Fidelity Models for Agile Flights in Unknown Environments

Autonomous navigation through unknown environments is a challenging task that entails real-time localization, perception, planning, and control. UAVs with this capability have begun to emerge in the literature with advances in lightweight sensing and computing. Although the planning methodologies vary from platform to platform, many algorithms adopt a hierarchical planning architecture where a slow, low-fidelity global planner guides a fast, high-fidelity local planner. However, in unknown environments, this approach can lead to erratic or unstable behavior due to the interaction between the global planner, whose solution is changing constantly, and the local planner; a consequence of not capturing higher-order dynamics in the global plan. This work proposes a planning framework in which multi-fidelity models are used to reduce the discrepancy between the local and global planner. Our approach uses high-, medium-, and low-fidelity models to compose a path that captures higher-order dynamics while remaining computationally tractable. In addition, we address the interaction between a fast planner and a slower mapper by considering the sensor data not yet fused into the map during the collision check. This novel mapping and planning framework for agile flights is validated in simulation and hardware experiments, showing replanning times of 5-40 ms in cluttered environments.Comment: ICRA 201

Recent Advances in Path Integral Control for Trajectory Optimization: An Overview in Theoretical and Algorithmic Perspectives

This paper presents a tutorial overview of path integral (PI) control approaches for stochastic optimal control and trajectory optimization. We concisely summarize the theoretical development of path integral control to compute a solution for stochastic optimal control and provide algorithmic descriptions of the cross-entropy (CE) method, an open-loop controller using the receding horizon scheme known as the model predictive path integral (MPPI), and a parameterized state feedback controller based on the path integral control theory. We discuss policy search methods based on path integral control, efficient and stable sampling strategies, extensions to multi-agent decision-making, and MPPI for the trajectory optimization on manifolds. For tutorial demonstrations, some PI-based controllers are implemented in MATLAB and ROS2/Gazebo simulations for trajectory optimization. The simulation frameworks and source codes are publicly available at https://github.com/INHA-Autonomous-Systems-Laboratory-ASL/An-Overview-on-Recent-Advances-in-Path-Integral-Control.Comment: 16 pages, 9 figure

FATROP : A Fast Constrained Optimal Control Problem Solver for Robot Trajectory Optimization and Control

Trajectory optimization is a powerful tool for robot motion planning and control. State-of-the-art general-purpose nonlinear programming solvers are versatile, handle constraints in an effective way and provide a high numerical robustness, but they are slow because they do not fully exploit the optimal control problem structure at hand. Existing structure-exploiting solvers are fast but they often lack techniques to deal with nonlinearity or rely on penalty methods to enforce (equality or inequality) path constraints. This works presents FATROP: a trajectory optimization solver that is fast and benefits from the salient features of general-purpose nonlinear optimization solvers. The speed-up is mainly achieved through the use of a specialized linear solver, based on a Riccati recursion that is generalized to also support stagewise equality constraints. To demonstrate the algorithm's potential, it is benchmarked on a set of robot problems that are challenging from a numerical perspective, including problems with a minimum-time objective and no-collision constraints. The solver is shown to solve problems for trajectory generation of a quadrotor, a robot manipulator and a truck-trailer problem in a few tens of milliseconds. The algorithm's C++-code implementation accompanies this work as open source software, released under the GNU Lesser General Public License (LGPL). This software framework may encourage and enable the robotics community to use trajectory optimization in more challenging applications

Contributions to Open Problems on Cable Driven Robots and Persistent Manifolds for the Synthesis of Mechanisms

Although many efforts are continuously devoted to the advancement of robotics, there are still many open and unresolved problems to be faced. This thesis, therefore, sets out to tackle some of them with the aim of scratching the surface and look a little further for new ideas or solutions. The topics covered are mainly two. The first part deals with the development and improvement of control techniques for cable-driven robots. The second focuses on the study of persistent manifolds seen as constituting aspects of theoretical kinematics. In detail, -Part I deals with cable-driven platforms. In it, both techniques for selecting cable tensions and the design of a robust controller are developed. The aim is, therefore, to enhance the two building blocks of the overall control scheme in order to improve the performance of these robots during the execution of tracking tasks. -- The first chapter introduces to open problems and recalls the main concepts necessary to understand the following chapters; -- the contribution of the second chapter consists of the introduction of the Analytic Centre. It allows the generation of continuous and differentiable tension profiles while taking into account non-linear phenomena such as friction in the computation of tensions to be applied; -- the third chapter, although still at a preliminary stage, introduces sensitivity for tension calculation methods, offering perspectives of considerable interest for tension control in the current scientific context; -- the fourth chapter proposes the design of an adaptive controller. It allows external disturbances and/or uncertainties in the model to be faced such that the task can be performed with as little error as possible. The controller architecture is the innovative peculiarity conferring autonomy to cable systems. Initially applied to counteract wind in aerial systems it is now also used for cable breakage scenarios; -- the conclusions, at first, draw together the results obtained. In addition, they emphasise the lack of the techniques introduced in order to outline possible future paths and topics that need further investigation. - Part II delves into theoretical kinematics. The discovery and classification of invariant screw systems shed light on numerous aspects of robot mobility and synthesis. Nevertheless, this generated the emergence of new ideas and questions that are still unresolved. Among them, one of the more notable concerns the identification and classification of 5-dimensional persistent manifolds. -- Similarly to the first part, the first chapter provides an overview of the problems addressed and the theoretical notions necessary to understand the subsequent contributions; -- the second chapter contributes by directly tackling the above-mentioned question by exploiting the properties of dual quaternions, the Study quadric and differential geometry. A library of 5-persistent varieties, so far missing in the literature, is presented along with theorems that complete and generalise previous ones in the literature; -- an original work, concerning line motions and synthesis of mechanisms that generate them, is reported in the third chapter as a spin-off of the studies on persistent manifolds; -- the conclusions wrap up the obtained results trying to highlight gaps and deficiencies to be dealt with in the future. Here, two small sections are dedicated to ongoing works regarding the persistence definition and the screw systems' invariants and subvariants

Geometric Control of two Quadrotors Carrying a Rigid Rod with Elastic Cables

This paper presents the design of a geometric trajectory tracking controller for the cooperative task of two quadrotor UAVs (unmanned aerial vehicles) carrying and transporting a rigid bar, which is attached to the quadrotors via inflexible elastic cables. The elasticity of the cables together with techniques of singular perturbation allows a reduction in the model to that of a similar model with inelastic cables. In this reduced model, we design a controller such that the rod exponentially tracks a given desired trajectory for its position and attitude, under some assumptions on initial error. We then show that exponential tracking in the reduced model corresponds to exponential tracking of the original elastic model. We also show that the previously defined control scheme provides uniform ultimate boundedness in the presence of unstructured bounded disturbances.Comment: 20 pages, 3 figure

NEPTUNE: Non-Entangling Planning for Multiple Tethered Unmanned Vehicles

Despite recent progress on trajectory planning of multiple robots and path planning of a single tethered robot, planning of multiple tethered robots to reach their individual targets without entanglements remains a challenging problem. In this paper, we present a complete approach to address this problem. Firstly, we propose a multi-robot tether-aware representation of homotopy, using which we can efficiently evaluate the feasibility and safety of a potential path in terms of (1) the cable length required to reach a target following the path, and (2) the risk of entanglements with the cables of other robots. Then, the proposed representation is applied in a decentralized and online planning framework that includes a graph-based kinodynamic trajectory finder and an optimization-based trajectory refinement, to generate entanglement-free, collision-free and dynamically feasible trajectories. The efficiency of the proposed homotopy representation is compared against existing single and multiple tethered robot planning approaches. Simulations with up to 8 UAVs show the effectiveness of the approach in entanglement prevention and its real-time capabilities. Flight experiments using 3 tethered UAVs verify the practicality of the presented approach.Comment: Accepted for publication in IEEE Transaction on Robotic