We present a formation controller for a team of mobile robots, modelled with double-integrator dynamics, to manipulate deformable objects grasped around their contour. The manipulation task is defined as reaching a target configuration consisting of a desired shape, scale, position and orientation of the formation in 2D, while preserving the integrity of the object. We provide a set of controllers designed to allow the uncoupled control of the variables that define the task. The formal analysis of the controllers is covered in depth in terms of uncoupling, stability and convergence to the equilibrium state. Besides, we include control barrier functions to enforce safety constraints relevant to the task, i.e., collision and excessive stretching avoidance. The performance of the method is illustrated in simulations and in real experiments.
In the problem of autonomous transport of deformable objects, we propose a multirobot approach for steering a large object to a target configuration (object dimensions, orientation, and position). Firstly, we present a deformation model based on the evolution over time of the dimensions and rotation of the object's bounding box (BB). We consider the object is grasped by a set of mobile robots with double-integrator dynamics. Then, we propose a set of nominal controllers that allows reaching a desired configuration of the BB that models the deformable object. In order to prevent collisions of the object with static or dynamic obstacles, we formulate a control barrier function (CBF) that exploits our deformation model. Finally, we integrate the nominal controllers and the CBF into a quadratic-programming controller, which includes overstretching avoidance and velocity constraints. We report simulation results to show the performance of this approach in different test scenarios.
Post-blast operations in tunnel construction represent a critical bottleneck due to mandatory downtime and hazardous environmental conditions. This study addresses these challenges by developing and validating an integrated cyber–physical architecture that coordinates an autonomous Unmanned Aerial Vehicle (UAV) and an Autonomous Wheel Loader (AWL) under the supervision of a Digital Twin acting as central operational digital interface. Specifically, this technology was designed to access the tunnel, evaluate post-blasting conditions, and initiate operations during mandatory exclusion periods for personnel. The system was validated in a realistic, Global Navigation Satellite System (GNSS)-denied tunnel environment emulating post-detonation visibility constraints. The results demonstrate that the aerial agent successfully navigated and mapped the excavation front in less than 8 min, establishing a shared coordinate system for the ground machinery. Through this collaborative workflow, the autonomous deployment enabled operations to commence 50% to 80% earlier than conventional manual procedures. Furthermore, the system reduced daily operational time by approximately 8%, with an estimated return on financial investment between one and seven months. Overall, the proposed framework eliminates human exposure during high-risk inspections and transforms the fragmented excavation cycle into a continuous, data-driven process.
The control of vehicles towing trailers is of significant interest to industry due to their wide-ranging applications across various sectors. Trailers play essential roles in logistics, mining, and other fields. This study focuses on the control of a dumper with a trailer specifically used for the monitoring of terrain stability in mining operations. The trailer is equipped with a radar system for detecting potential ground shifts that could jeopardize fieldwork safety. While numerous studies have addressed the control of Ackerman vehicles and trailers, this dumper presents a unique challenge due to its rear-axle steering mechanism. Due to this configuration, which has not been extensively studied in the literature, although the differential flatness of the system is proven, computation of the flat outputs leads to a system of partial differential equations that cannot be solved analytically. For this reason, this paper examines partial feedback linearization to facilitate control and proposes a solution for trajectory tracking that also stabilizes jack-knifing tendencies between the vehicle and trailer. The designed control system was successfully validated in a virtual environment.