Bearing-based formation control with second-order agent dynamics

We consider the distributed formation control problem for a network of agents using visual measurements. We propose solutions that are based on bearing (and optionally distance) measurements, and agents with double integrator dynamics. We assume that a subset of the agents can track, in addition to their neighbors, a set of static features in the environment. These features are not considered to be part of the formation, but they are used to asymptotically control the velocity of the agents. We analyze the convergence properties of the proposed protocols analytically and through simulations.Published versionSupporting documentatio

Bearing-only formation control with auxiliary distance measurements, leaders, and collision avoidance

We address the controller synthesis problem for distributed formation control. Our solution requires only relative bearing measurements (as opposed to full translations), and is based on the exact gradient of a Lyapunov function with only global minimizers (independently from the formation topology). These properties allow a simple proof of global asymptotic convergence, and extensions for including distance measurements, leaders and collision avoidance. We validate our approach through simulations and comparison with other stateof-the-art algorithms.ARL grant W911NF-08-2-0004, ARO grant W911NF-13-1-0350, ONR grants N00014-07-1-0829, N00014-14-1-0510, N00014-15-1-2115, NSF grant IIS-1426840, CNS-1521617 and United Technologies

Distributed relative localization using the multi-dimensional weighted centroid

A key problem in multi-agent systems is the distributed estimation of the localization of agents in a common reference from relative measurements. Estimations can be referred to an anchor node or, as we do here, referred to the weighted centroid of the multi-agent system. We propose a Jacobi Over—Relaxation method for distributed estimation of the weighted centroid of the multi-agent system from noisy relative measurements. Contrary to previous approaches, we consider relative multidimensional measurements with general covariance matrices not necessarily diagonal. We prove our weighted centroid method converges faster than anchor-based solutions. We also analyze the method convergence and provide mathematical constraints that ensure avoiding ringing phenomena

Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments

This paper presents two novel control methodologies for the cooperative manipulation of an object by N robotic agents. Firstly, we design an adaptive control protocol which employs quaternion feedback for the object orientation to avoid potential representation singularities. Secondly, we propose a control protocol that guarantees predefined transient and steady-state performance for the object trajectory. Both methodologies are decentralized, since the agents calculate their own signals without communicating with each other, as well as robust to external disturbances and model uncertainties. Moreover, we consider that the grasping points are rigid, and avoid the need for force/torque measurements. Load distribution is also included via a grasp matrix pseudo-inverse to account for potential differences in the agents' power capabilities. Finally, simulation and experimental results with two robotic arms verify the theoretical findings

Robotite halduri alamsüsteemi väljatöötamine tarkvararaamistikule TEMOTO

Robots provide an opportunity to spare humans from tasks that are repetitive, require high precision or involve hazardous environments. Robots are often composed of multiple robotic units, such as mobile manipulators that integrate object manipulation and traversal capabilities. Additionally, a group of robots, i.e., multi robot systems, can be utilized for solving a common goal. However, the more elements are added to the system, the more complicated it is to control it. TeMoto is a ROS package intended for developing human-robot collaboration and multi-robot applications where TeMoto Robot Manager (TRM), a subsystem of TeMoto, is designed to unify the control of main robotic components: manipulators, mobile bases and grippers. However the implementation of TRM was incomplete prior to this work, having no functionality for controlling mobile bases and grippers. This thesis extends the functionality of TeMoto Robot Manager by implementing the aforementioned missing features, thus facilitating the integration of compound robots and multi-robot systems. The outcome of this work is demonstrated in an object transportation scenario incorporating a heterogeneous multi-robot system that consists of two manipulators, two grippers, and a mobile base. In estonian: Robotid võimaldavad aidata inimesi ülesannetes mis on eluohtlikud, nõuavad suurt täpsust või on üksluised. Üks terviklik robot koosneb tihtipeale mitme eri funktsionaalsusega alamrobotist, millest näiteks mobiilne manipulaator on kombinatsioon mobiilsest platvormist ja objektide manipuleerimise võimekusega robotist. Roboteid saab rakendada ülesannete lahendamisel ka mitme roboti süsteemina, kuid robotite hulga suurenemisel suureneb ka nende haldamise keerukus. TeMoto on ROSi kimp, mis hõlbustab inimene-robot koostöö ja mitme roboti süsteemide arendamist. Robotite haldur on TeMoto alamsüsteem, mis aitab käsitleda mobiilseid platvorme, manipulaatoreid ja haaratseid ühtse tervikliku robotina. Käesolevale tööle eelnevalt puudus Robotite halduril mobiilsete platvormide ja haaratsite haldamise võimekused, mille väljatöötamine oli antud töö peamiseks eesmärgiks. Töö tulemusena valmis TeMoto Robotite halduri terviklik lahendus, mille funktsionaalsust demonstreeriti objekti transportimise ülesande lahendamisel, kaasates kahest manipulaatorist, kahest haaratsist ja mobiilsest platvormist koosnevat heterogeenset mitme roboti süsteemi

Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies

In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in $SE(3)$. The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller's behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller's performance using numerical simulations of a manipulation task in 3D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions

Decentralized Motion Control for Cooperative Manipulation with a Team of Networked Mobile Manipulators

International audienceIn this paper we consider the cooperative control of the manipulation of a load on a plane by a team of mobile robots. We propose two different novel solutions. The first is a controller which ensures exact tracking of the load twist. This controller is partially decentralized since, locally, it does not rely on the state of all the robots but needs only to know the system parameters and load twist. Then we propose a fully decentralized controller that differs from the first one for the use of i) a decentralized estimation of the parameters and twist of the load based only on local measurements of the velocity of the contact points and ii) a discontinuous robustification term in the control law. The second controller ensures a practical stabilization of the twist in presence of estimation errors. The theoretical results are finally corroborated with a simulation campaign evaluating different manipulation settings