A Survey on Passing-through Control of Multi-Robot Systems in Cluttered Environments

This survey presents a comprehensive review of various methods and algorithms related to passing-through control of multi-robot systems in cluttered environments. Numerous studies have investigated this area, and we identify several avenues for enhancing existing methods. This survey describes some models of robots and commonly considered control objectives, followed by an in-depth analysis of four types of algorithms that can be employed for passing-through control: leader-follower formation control, multi-robot trajectory planning, control-based methods, and virtual tube planning and control. Furthermore, we conduct a comparative analysis of these techniques and provide some subjective and general evaluations.Comment: 18 pages, 19 figure

Downwash-Aware Trajectory Planning for Large Quadrotor Teams

We describe a method for formation-change trajectory planning for large quadrotor teams in obstacle-rich environments. Our method decomposes the planning problem into two stages: a discrete planner operating on a graph representation of the workspace, and a continuous refinement that converts the non-smooth graph plan into a set of C^k-continuous trajectories, locally optimizing an integral-squared-derivative cost. We account for the downwash effect, allowing safe flight in dense formations. We demonstrate the computational efficiency in simulation with up to 200 robots and the physical plausibility with an experiment with 32 nano-quadrotors. Our approach can compute safe and smooth trajectories for hundreds of quadrotors in dense environments with obstacles in a few minutes.Comment: 8 page

Connectivity Preservation in Multi-Agent Systems using Model Predictive Control

Flocking of multiagent systems is one of the basic behaviors in the field of control of multiagent systems and it is an essential element of many real-life applications. Such systems under various network structures and environment modes have been extensively studied in the past decades. Navigation of agents in a leader-follower structure while operating in environments with obstacles is particularly challenging. One of the main challenges in flocking of multiagent systems is to preserve connectivity. Gradient descent method is widely utilized to achieve this goal. But the main shortcoming of applying this method for the leader-follower structure is the need for continuous data transmission between agents and/or the preservation of a fixed connection topology. In this research, we propose an innovative model predictive controller based on a potential field that maintains the connectivity of a flock of agents in a leader-follower structure with dynamic topology. The agents navigate through an environment with obstacles that form a path leading to a certain target. Such a control technique avoids collisions of followers with each other without using any communication links while following their leader which navigates in the environment through potential functions for modelling the neighbors and obstacles. The potential field is dynamically updated by introducing weight variables in order to preserve connectivity among the followers as we assume only the leader knows the target position. The values of these weights are changed in real-time according to trajectories of the agents when the critical neighbors of each agent is determined. We compare the performance of our predictive-control based algorithm with other approaches. The results show that our algorithm causes the agents to reach the target in less time. However, our algorithm faces more deadlock cases when the agents go through relatively narrow paths. Due to the consideration of the input costs in our controller, the group of agents reaching the target faster does not necessarily result in the followers consuming more energy than the leader

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies