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Learning-Based Multi-UAV Flocking Control With Limited Visual Field and Instinctive Repulsion

Bai, Chengchao (author), Yan, Peng (author), Piao, Haiyin (author), Pan, W. (author), Guo, Jifeng (author)

This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...

journal article 2024

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Energy-Efficient Routing of a Multirobot Station: A Flexible Time-Space Network Approach

Xin, Jianbin (author), Meng, Chuang (author), D'Ariano, Andrea (author), Schulte, F. (author), Peng, Jinzhu (author), Negenborn, R.R. (author)

This paper investigates a novel routing problem of a multi-robot station in a manufacturing cell. In the existing literature, the objective is to minimize the cycle time or energy consumption separately. The routing problem considered in this paper aims to reduce the cycle time and energy consumption jointly for each robot while avoiding...

journal article 2023

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Distributed Nonlinear Trajectory Optimization for Multi-Robot Motion Planning

Ferranti, L. (author), Lyons, L. (author), Negenborn, R.R. (author), Keviczky, T. (author), Alonso-Mora, J. (author)

This work presents a method for multi-robot coordination based on a novel distributed nonlinear model predictive control (NMPC) formulation for trajectory optimization and its modified version to mitigate the effects of packet losses and delays in the communication among the robots. Our algorithms consider that each robot is equipped with an...

journal article 2023

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Speed and heading control-based collision avoidance for a ship towing system

Zhang, Lei (author), Liu, Wenjie (author), Du, Zhe (author), Du, Lei (author), Li, Xiaobin (author)

Collision avoidance is a priority task for ensuring the safety of a maritime transportation system. However, for a ship towing system, which is characterized by multiple vessels and physical connections, the research works about collision avoidance is limited. Thus, this paper proposes a speed and heading control-based conflict resolution of...

journal article 2023

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Learning to Play Trajectory Games Against Opponents with Unknown Objectives

Liu, Xinjie (author), Peters, L. (author), Alonso-Mora, J. (author)

Many autonomous agents, such as intelligent vehicles, are inherently required to interact with one another. Game theory provides a natural mathematical tool for robot motion planning in such interactive settings. However, tractable algorithms for such problems usually rely on a strong assumption, namely that the objectives of all players in...

journal article 2023

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Robotic Monitoring of Habitats: the Natural Intelligence Approach

Angelini, Franco (author), Angelini, Pierangela (author), Angiolini, Claudia (author), Bagella, Simonetta (author), Caccianiga, Marco (author), Della Santina, C. (author), Gigante, Daniela (author), Hutter, Marco (author), Nanayakkara, Thrishantha (author)

In this paper, we first discuss the challenges related to habitat monitoring and review possible robotic solutions. Then, we propose a framework to perform terrestrial habitat monitoring exploiting the mobility of legged robotic systems. The idea is to provide the robot with the Natural Intelligence introduced as the combination of the...

journal article 2023

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Learning scalable and efficient communication policies for multi-robot collision avoidance

Serra Gomez, A. (author), Zhu, H. (author), Ferreira de Brito, B.F. (author), Böhmer, J.W. (author), Alonso-Mora, J. (author)

Decentralized multi-robot systems typically perform coordinated motion planning by constantly broadcasting their intentions to avoid collisions. However, the risk of collision between robots varies as they move and communication may not always be needed. This paper presents an efficient communication method that addresses the problem of “when...

journal article 2023

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Group-Based Distributed Auction Algorithms for Multi-Robot Task Assignment

Bai, X. (author), Fielbaum, Andres (author), Kronmüller, M. (author), Knödler, L. (author), Alonso-Mora, J. (author)

This paper studies the multi-robot task assignment problem in which a fleet of dispersed robots needs to efficiently transport a set of dynamically appearing packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity. Given a...

journal article 2023

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A conflict cluster-based method for collision avoidance decision-making in multi-ship encounter situations

Liu, Kezhong (author), Wu, Xiaolie (author), Zhou, Y. (author), Yuan, Zhitao (author), Yang, Xing (author), Xin, Xuri (author), Zhuang, Sujie (author)

During the process of collision avoidance, especially in a multi-ship encounter situation, the dynamic interactions among individual ships impose a significant impact on collision avoidance decision-making. It is imperative, therefore, that collision avoidance decisions are formulated with a comprehensive consideration of not only the current...

journal article 2023

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Decentralized probabilistic multi-robot collision avoidance using buffered uncertainty-aware Voronoi cells

Zhu, H. (author), Ferreira de Brito, B.F. (author), Alonso-Mora, J. (author)

In this paper, we present a decentralized and communication-free collision avoidance approach for multi-robot systems that accounts for both robot localization and sensing uncertainties. The approach relies on the computation of an uncertainty-aware safe region for each robot to navigate among other robots and static obstacles in the...

journal article 2022

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COLREGS-Compliant collision avoidance for physically coupled multi-vessel systems with distributed MPC

Du, Zhe (author), Negenborn, R.R. (author), Reppa, V. (author)

This paper proposes a distributed control scheme for autonomous tugboats to tow a ship in a restricted water traffic environment ensuring collision avoidance while being compliant with maritime regulation called COLREGS. The complex problem is cooperatively solved by addressing three sub-optimization problems. The first is to optimize the...

journal article 2022

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Model-Reference Reinforcement Learning for Collision-Free Tracking Control of Autonomous Surface Vehicles

Zhang, Q. (author), Pan, W. (author), Reppa, V. (author)

This paper presents a novel model-reference reinforcement learning algorithm for the intelligent tracking control of uncertain autonomous surface vehicles with collision avoidance. The proposed control algorithm combines a conventional control method with reinforcement learning to enhance control accuracy and intelligence. In the proposed...

journal article 2021

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Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery

Chen, Zhe (author), Alonso-Mora, J. (author), Bai, X. (author), Harabor, Daniel Damir (author), Stuckey, Peter James (author)

Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where a team of robots is tasked with transporting a set of tasks, each from an initial location and each to a specified target location. Appearing in the context of automated warehouse logistics and automated mail sortation, MAPD requires first deciding which robot is...

journal article 2021

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Where to go next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments

Ferreira de Brito, B.F. (author), Everett, Michael (author), How, Jonathan Patrick (author), Alonso-Mora, J. (author)

Robotic navigation in environments shared with other robots or humans remains challenging because the intentions of the surrounding agents are not directly observable and the environment conditions are continuously changing. Local trajectory optimization methods, such as model predictive control (MPC), can deal with those changes but require...

journal article 2021

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Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments

Zhu, H. (author), Martinez Claramunt, Francisco (author), Ferreira de Brito, B.F. (author), Alonso-Mora, J. (author)

This paper presents a data-driven decentralized trajectory optimization approach for multi-robot motion planning in dynamic environments. When navigating in a shared space, each robot needs accurate motion predictions of neighboring robots to achieve predictive collision avoidance. These motion predictions can be obtained among robots by...

journal article 2021

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Scenario-Based Trajectory Optimization in Uncertain Dynamic Environments

de Groot, O.M. (author), Ferreira de Brito, B.F. (author), Ferranti, L. (author), Gavrila, D. (author), Alonso-Mora, J. (author)

We present an optimization-based method to plan the motion of an autonomous robot under the uncertainties associated with dynamic obstacles, such as humans. Our method bounds the marginal risk of collisions at each point in time by incorporating chance constraints into the planning problem. This problem is not suitable for online optimization...

journal article 2021

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Integrated nonlinear model predictive control for automated driving

Chowdhri, Nishant (author), Ferranti, L. (author), Santafé Iribarren, Felipe (author), Shyrokau, B. (author)

This work presents a Nonlinear Model Predictive Control (NMPC) scheme to perform evasive maneuvers and avoid rear-end collisions. Rear-end collisions are among the most common road fatalities. To reduce the risk of collision, it is necessary for the controller to react as quickly as possible and exploit the full vehicle maneuverability (i.e.,...

journal article 2021

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Online trajectory planning and control of a MAV payload system in dynamic environments

Potdar, N.D. (author), de Croon, G.C.H.E. (author), Alonso-Mora, J. (author)

Micro Aerial Vehicles (MAVs) can be used for aerial transportation in remote and urban spaces where portability can be exploited to reach previously inaccessible and inhospitable spaces. Current approaches for path planning of MAV swung payload system either compute conservative minimal-swing trajectories or pre-generate agile collision-free...

journal article 2020

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Optimizing the joint collision avoidance operations of multiple ships from an overall perspective

Li, Shijie (author), Liu, Jialun (author), Negenborn, R.R. (author), Ma, Feng (author)

Ship collision is the main type of maritime accidents, which causes great losses on human lives and economy, and brings negative impacts to the maritime environment. In crowded waters such as the sea area near a seaport, multiple ships encountering situations happen frequently. While several methods have been proposed for solving multiple...

journal article 2019

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A forward collision avoidance algorithm based on driver braking behavior

Xiong, Xiaoxia (author), Wang, M. (author), Cai, Yingfeng (author), Cheng, Long (author), Farah, H. (author), Hagenzieker, Marjan (author)

Measuring risk is critical for collision avoidance. The paper aims to develop an online risk level classification algorithm for forward collision avoidance systems. Assuming risk levels are reflected by braking profiles, deceleration curves from critical evasive braking events from the Virginia “100-car” database were first extracted. The...

journal article 2019