相关论文: Deadlock-Free Collision Avoidance for Nonholonomic…

Trajectory planning for multiple robots in shared environments is a challenging problem especially when there is limited communication available or no central entity. In this article, we present Real-time planning using Linear Spatial…

Network-on-chips (NoCs) are currently a widely used approach for achieving scalability of multi-cores to many-cores, as well as for interconnecting other vital system-on-chip (SoC) components. Each entity in 2D mesh-based NoCs has a router…

Collision avoidance for multirobot systems is a well-studied problem. Recently, control barrier functions (CBFs) have been proposed for synthesizing controllers that guarantee collision avoidance and goal stabilization for multiple robots.…

This paper introduces a neural Nonlinear Model Predictive Control (NMPC) framework for mapless, collision-free navigation in unknown environments with Aerial Robots, using onboard range sensing. We leverage deep neural networks to encode a…

We propose a novel methodology for robotic follow-ahead applications that address the critical challenge of obstacle and occlusion avoidance. Our approach effectively navigates the robot while ensuring avoidance of collisions and occlusions…

This work presents a distributed method for multi-vehicle coordination based on nonlinear model predictive control (NMPC) and dual decomposition. Our approach allows the vehicles to coordinate in tight spaces (e.g., busy highway lanes or…

Nonholonomic mechanical systems encompass a large class of practically interesting robotic structures, such as wheeled mobile robots, space manipulators, and multi-fingered robot hands. However, few results exist on the cooperative control…

In environments where multiple robots must coordinate in a shared space, decentralized approaches allow for decoupled planning at the cost of global guarantees, while centralized approaches make the opposite trade-off. These solutions make…

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an…

We study the problem of multi-agent navigation in static environments when no centralized controller is present. Each agent is controlled individually and relies on three algorithmic components to achieve its goal while avoiding collisions…

We study the problem of motion-planning for free-flying multi-link robots and develop a sampling-based algorithm that is specifically tailored for the task. Our work is based on the simple observation that the set of configurations for…

The need for fully autonomous mobile robots has surged over the past decade, with the imperative of ensuring safe navigation in a dynamic setting emerging as a primary challenge impeding advancements in this domain. In this paper, a Safety…

A novel decentralised trajectory generation algorithm for Multi Agent systems is presented. Multi-robot systems have the capacity to transform lives in a variety of fields. But, trajectory generation for multi-robot systems is still in its…

In multi-robot systems where a central decision maker is specifying the movement of each individual robot, a communication failure can severely impair the performance of the system. This paper develops a motion strategy that allows robots…

For active intervention tasks in underwater environments, the use of autonomous vehicles is just now emerging as an active area of research. During operation, for various reasons, the robot might find itself on a collision course with an…

This paper addresses the problem of pushing manipulation with nonholonomic mobile robots. Pushing is a fundamental skill that enables robots to move unwieldy objects that cannot be grasped. We propose a stable pushing method that maintains…

This paper proposes a new algorithm for collision-free coverage control of multiple non-cooperating swarms in the presence of bounded disturbances. A new methodology is introduced that accounts for uncertainties in disturbance measurements.…

Robots need to predict and react to human motions to navigate through a crowd without collisions. Many existing methods decouple prediction from planning, which does not account for the interaction between robot and human motions and can…

This paper introduces a novel classification for Autonomous Mobile Robots (AMRs), into three phases and five steps, focusing on autonomous collision-free navigation. Additionally, it presents the main methods and widely accepted…

We deal with the problem of planning collision-free trajectories for robots operating in a shared space. Given the start and destination position for each of the robots, the task is to find trajectories for all robots that reach their…