The increasingly widespread use of autonomous mobile robots in scenarios such as surveillance, search and rescue, and logistics requires navigation strategies that guarantee safety, robustness, and feasibility even in the presence of stringent constraints, external disturbances, model uncertainties, and communication delays. This research focuses on the development of set-theoretic methodologies for trajectory and motion planning of remotely controlled skid-steered tracked mobile robots, with the aim of ensuring the feasibility and safety of navigation in the presence of model uncertainties, external disturbances, and actuation constraints in complex environments. Two methods are proposed that solve the problem of safe navigation in the presence of model uncertainties, external disturbances, and actuation constraints for the single-robot case, and two methods that solve the problem of safe navigation in the presence of model uncertainties, external disturbances, and actuation constraints for multi-robot systems, to which are added the crucial challenges of coordination management and collision prevention to maintain safe and cooperative operations. The main contributions of the work are: (i) A Set-Theoretic Feasible Trajectory Planning (ST-FTP) Method for skid-steered tracked mobile robots subject to sliding phenomena and controlled through a communication network (NCS) based on graphs and feasibility conditions formulated as semidefinite programming (SDP) problems with Linear Matrix Inequalities (LMIs) constrains; the objective of the method is to generate trajectories composed of a sequence of straight segments, each to be traveled at a desired speed, which ensure that the robot maintains a predetermined safety distance from any obstacle in the operating environment, regardless of the model uncertainties, the external disturbances, and the actuation constraints, guaranteeing that these trajectories are dynamically achievable by the system. (ii) A Set-Theoretic Model Predictive Control (ST-MPC) Method that addresses the problem by ensuring safe navigation from the initial state to the target state, while managing uncertainties, external disturbances, and network-induced delays using set-theoretic arguments. Model predictive control (MPC) based on set-theoretic arguments is capable of handling unexpected obstacles, network delays, and dynamic uncertainties, ensuring compliance with constraints and safety. The contribution exploits the ideas of receding horizon set-based control and customizes them according to the proposed framework, in which at every moment in time, information about the obstacle-free region is subject to inevitable latency phenomena. (iii) A Set-Theoretic Feasible Coordinated Trajectory Planning (ST-FCTP) Method that aims to plan optimal trajectories that robustly guarantee the absence of collisions during the movement of the robots along assigned feasible trajectories, explicitly considering the presence of errors in the trajectory tracking. The coordinated planning method for multi-robot systems integrates disturbances and uncertainties in the planning phase through a graph search problem and LMI constraints; The key aspect of the contribution leads in the fact that the collision avoidance aspects are addressed by resorting to set-theoretic arguments, while the trajectory planning aspects are reformulated in terms of solving a mixed graph search problem and solving SDP problems with constraints expressed by LMIs constrains. (iv) A Set-theoretic Time-based Trajectory Synchronization (ST-TBTS) methodology for temporal synchronization of trajectories, formulated as an LMI optimization problem, which minimizes the occupancy of the shared common spaces while ensuring feasibility and robustness. Collision avoidance and coordination are achieved through synchronization of robot trajectories by imposing delays on platform departures. The procedure exploits the trajectory's feasibility property by solving optimization problems involving LMIs constraints. The algorithm operates in separate offline and online phases. In the offline phase, the time delay intervals useful for synchronization are calculated based on the planned feasible trajectories. Then, in the online phase, the actual delay is calculated by solving a linear programming (LP) optimization problem that minimizes the occupancy time of the shared operational space. All the proposed methodologies have been validated through extensive numerical simulations and real-world experiments using skid-steered tracked mobile robots available at the Automatic Control Laboratory of the Mediterranean University of Reggio Calabria.
L'uso sempre più diffuso di robot autonomi in scenari quali sorveglianza, ricerca e soccorso e logistica richiede strategie di navigazione che garantiscano sicurezza, robustezza e fattibilità anche in presenza di vincoli di attuazione rigorosi, disturbi esterni, incertezze di modello e ritardi di comunicazione. Questa ricerca si concentra sullo sviluppo di metodologie basate sulla teoria degli insiemi (set-theoretic) per la pianificazione della traiettoria e del movimento di robot mobili cingolati a guida differenziale controllati da remoto con l'obiettivo di garantire la feasibility e la sicurezza della navigazione in presenza di incertezze del modello, disturbi esterni e vincoli di attuazione in ambienti complessi. Vengono proposti due metodi che risolvono il problema della navigazione sicura in presenza di incertezze del modello, disturbi esterni e vincoli di attuazione per il caso di un singolo robot, e due metodi che risolvono il problema della navigazione sicura in presenza di incertezze del modello, disturbi esterni e vincoli di attuazione per sistemi multi-robot, ai quali si aggiungono le sfide cruciali della gestione del coordinamento e della prevenzione delle collisioni. I principali contributi del lavoro possono essere riassunti come segue: (i) Un metodo Set-Theoretic Feasible Trajectory Planning (ST-FTP) per la pianificazione di traiettorie feasible per robot cingolati a guida differenziale soggetti a fenomeni di slittamento, e controllati attraverso una rete di comunicazione, basato su algoritmi di ricerca su grafo e condizioni di feasibility formulate come problemi di programmazione semidefinita (SDP)con vincoli formulati sottoforma di disequazioni lineari di matrici (LMI); l'obiettivo del metodo è quello di generare traiettorie composte da una sequenza di segmenti rettilinei, ciascuno da percorrere alla velocità desiderata assegnata, che assicurano che il robot mantenga una distanza di sicurezza predeterminata da qualsiasi ostacolo nell'ambiente operativo, indipendentemente dalle incertezze del modello, dai disturbi esterni e dai vincoli di attuazione, garantendo che tali traiettorie siano dinamicamente realizzabili dal sistema. (ii) Un metodo Set-Theoretic Model Predictive Control (ST-MPC) che affronta il problema garantendo una navigazione sicura dallo stato iniziale allo stato finale, gestendo al contempo le incertezze di modello, i disturbi esterni e i ritardi indotti dalla rete di comunicazione, utilizzando argomenti set-theoretic. Il controllo predittivo set-theoretic è capace di gestire ostacoli imprevisti, ritardi di rete e incertezze dinamiche, garantendo il rispetto dei vincoli e la sicurezza. Il contributo sfrutta le idee del controllo basato su insiemi a orizzonte recedente e le personalizza in base al quadro proposto, in cui in ogni momento le informazioni sulla regione priva di ostacoli sono soggette a inevitabili fenomeni di latenza. (iii) Un metodo Set-Theoretic Feasible Coordinated Trajectory Planning (ST-FCTP) per sistemi multirobot che mira a pianificare traiettorie ottimali coordinate che garantiscano in modo robusto l'assenza di collisioni durante il movimento dei robot lungo traiettorie fattibili assegnate, considerando esplicitamente la presenza di errori nel tracciamento della traiettoria. Il metodo di pianificazione coordinata per sistemi multi-robot integra disturbi e incertezze nella fase di pianificazione attraverso un problema di ricerca su grafo e vincoli LMI; l'aspetto chiave del contributo risiede nel fatto che gli aspetti relativi alla prevenzione delle collisioni vengono affrontati ricorrendo ad argomenti set-theoretic, mentre gli aspetti relativi alla pianificazione della traiettoria vengono riformulati in termini di risoluzione di un problema di ricerca su grafo e di risoluzione di problemi SDP con vincoli espressi da LMI. (iv) Un metodo Set-theoretic Time-based Trajectory Synchronization (ST-TBTS) per la sincronizzazione temporale delle traiettorie, formulata come un problema di ottimizzazione LMI, che riduce al minimo l'occupazione degli spazi comuni condivisi garantendo al contempo fattibilità e robustezza. L'evitamento delle collisioni e il coordinamento delle piattaforme sono ottenuti attraverso la sincronizzazione delle traiettorie dei robot schedulandone opportunamente le partenze. La procedura sfrutta la proprietà di feasibility della traiettoria risolvendo problemi di ottimizzazione che coinvolgono vincoli LMI. L'algoritmo opera in fasi separate offline e online. Nella fase offline, gli intervalli di ritardo utili per la sincronizzazione vengono calcolati sulla base delle traiettorie feasible pre-pianificate. Successivamente, nella fase online, il ritardo effettivo imposto per ogni piattaforma viene calcolato risolvendo un problema di ottimizzazione che riduce al minimo il tempo di occupazione dello spazio operativo condiviso. Tutte le metodologie proposte sono state validate tramite simulazioni numeriche e sperimentali con piattaforme reali disponibili presso il Laboratorio di Controlli Automatici dell'Università Mediterranea di Reggio Calabria.
SET-THEORETIC MOTION PLANNING FOR SKID-STEERED TRACKED ROBOTS. From Single to Coordinated Multi-Robot Systems under Constraint, Uncertainties, and Disturbances in Complex Scenarios / Ferraro, A.. - (2026 Apr 28).
SET-THEORETIC MOTION PLANNING FOR SKID-STEERED TRACKED ROBOTS. From Single to Coordinated Multi-Robot Systems under Constraint, Uncertainties, and Disturbances in Complex Scenarios
Ferraro, Alessia
2026-04-28
Abstract
The increasingly widespread use of autonomous mobile robots in scenarios such as surveillance, search and rescue, and logistics requires navigation strategies that guarantee safety, robustness, and feasibility even in the presence of stringent constraints, external disturbances, model uncertainties, and communication delays. This research focuses on the development of set-theoretic methodologies for trajectory and motion planning of remotely controlled skid-steered tracked mobile robots, with the aim of ensuring the feasibility and safety of navigation in the presence of model uncertainties, external disturbances, and actuation constraints in complex environments. Two methods are proposed that solve the problem of safe navigation in the presence of model uncertainties, external disturbances, and actuation constraints for the single-robot case, and two methods that solve the problem of safe navigation in the presence of model uncertainties, external disturbances, and actuation constraints for multi-robot systems, to which are added the crucial challenges of coordination management and collision prevention to maintain safe and cooperative operations. The main contributions of the work are: (i) A Set-Theoretic Feasible Trajectory Planning (ST-FTP) Method for skid-steered tracked mobile robots subject to sliding phenomena and controlled through a communication network (NCS) based on graphs and feasibility conditions formulated as semidefinite programming (SDP) problems with Linear Matrix Inequalities (LMIs) constrains; the objective of the method is to generate trajectories composed of a sequence of straight segments, each to be traveled at a desired speed, which ensure that the robot maintains a predetermined safety distance from any obstacle in the operating environment, regardless of the model uncertainties, the external disturbances, and the actuation constraints, guaranteeing that these trajectories are dynamically achievable by the system. (ii) A Set-Theoretic Model Predictive Control (ST-MPC) Method that addresses the problem by ensuring safe navigation from the initial state to the target state, while managing uncertainties, external disturbances, and network-induced delays using set-theoretic arguments. Model predictive control (MPC) based on set-theoretic arguments is capable of handling unexpected obstacles, network delays, and dynamic uncertainties, ensuring compliance with constraints and safety. The contribution exploits the ideas of receding horizon set-based control and customizes them according to the proposed framework, in which at every moment in time, information about the obstacle-free region is subject to inevitable latency phenomena. (iii) A Set-Theoretic Feasible Coordinated Trajectory Planning (ST-FCTP) Method that aims to plan optimal trajectories that robustly guarantee the absence of collisions during the movement of the robots along assigned feasible trajectories, explicitly considering the presence of errors in the trajectory tracking. The coordinated planning method for multi-robot systems integrates disturbances and uncertainties in the planning phase through a graph search problem and LMI constraints; The key aspect of the contribution leads in the fact that the collision avoidance aspects are addressed by resorting to set-theoretic arguments, while the trajectory planning aspects are reformulated in terms of solving a mixed graph search problem and solving SDP problems with constraints expressed by LMIs constrains. (iv) A Set-theoretic Time-based Trajectory Synchronization (ST-TBTS) methodology for temporal synchronization of trajectories, formulated as an LMI optimization problem, which minimizes the occupancy of the shared common spaces while ensuring feasibility and robustness. Collision avoidance and coordination are achieved through synchronization of robot trajectories by imposing delays on platform departures. The procedure exploits the trajectory's feasibility property by solving optimization problems involving LMIs constraints. The algorithm operates in separate offline and online phases. In the offline phase, the time delay intervals useful for synchronization are calculated based on the planned feasible trajectories. Then, in the online phase, the actual delay is calculated by solving a linear programming (LP) optimization problem that minimizes the occupancy time of the shared operational space. All the proposed methodologies have been validated through extensive numerical simulations and real-world experiments using skid-steered tracked mobile robots available at the Automatic Control Laboratory of the Mediterranean University of Reggio Calabria.| File | Dimensione | Formato | |
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