Proceedings

G. Li, B. Gabrich, D. Saldaña, J. Das, V. Kumar, and M. Yim "ModQuad-Vi: A Vision-Based Self-Assembling Modular Quadrotor"
ICRA'2019 - IEEE International Conference on Robotics and Automation.

Abstract

Flying modular robots have the potential to rapidly form temporary structures. In the literature, docking actions rely on external systems and indoor infrastructures for relative pose estimation. In contrast to related work, we provide local estimation during the self-assembly process to avoid dependency on external systems. In this paper, we introduce ModQuad-Vi, a flying modular robot that is aimed to operate in outdoor environments. We propose a new robot design and vision-based docking method. Our design is based on a quadrotor platform with onboard computation and visual perception. Our vision-based control method is able to accurately align modules for docking actions. Additionally, we present the dynamics and a geometric controller for the aerial modular system. Experiments validate the vision-based docking method with successful results.

D. Saldaña, B. Gabrich, G. Li, M. Yim, and V. Kumar "ModQuad: The Flying Modular Structure that Self-Assembles in Midair"
ICRA'2018 - IEEE International Conference on Robotics and Automation.

Abstract

We introduce ModQuad, a novel flying modular robotic structure that is able to self-assemble in midair and cooperatively fly. The structure is composed by agile flying modules that can easily move in a three dimensional environment. The module is based on a quadrotor platform within a cuboid frame which allows it to attach to other modules by matching vertical faces. Using this mechanism, a ModQuad swarm is able to rapidly assemble flying structures in midair using the robot bodies as building units. In this paper, we focus on two important tasks for modular flying structures. First, we propose a decentralized modular attitude controller to allow a team of physically connected modules to fly cooperatively. Second, we develop a docking method that drives pairs of structures to be attached in midair. Our method precisely aligns, and corrects motion errors during the docking process. In our experiments, we tested and analyzed the performance of the cooperative flying method for multiple configurations. We also tested the docking method with successful results.
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B. Gabrich, D. Saldaña, M. Yim, and V. Kumar "A Flying Gripper Based on Cuboid Modular Robots"
ICRA'2018 - IEEE International Conference on Robotics and Automation.

Abstract

We present a novel flying modular platform capable of grasping and transporting objects. It is composed of four cooperative identical modules where each is based on a quadrotor within a cuboid frame with a docking mechanism. Pairs of modules are able to fly independently and physically connect by matching their vertical edges forming a hinge. Four one degree of freedom (DOF) connections results in a one DOF four-bar linkage that can be used to grasp external objects. In this paper, we propose a decentralized method that allows the Flying Gripper to control its position, attitude and aperture angle. In our experiments, we tested the hovering performance for different aperture angles and with a grasped object. The performance for a closing and opening motion was also verified.
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D. Saldaña, R. Assunção, M. Hsieh, M.F.M. Campos, and V. Kumar "Cooperative Prediction of Time-Varying Boundaries with a Team of Robots"
MRS'2017 - International Symposium on Multi-Robot and Multi-Agent Systems.

Abstract

Environmental boundaries, such as the borderline of a forest fire or an oil spill, pose a significant threat for living organisms. Anticipating the dynamics of these phenomena is a potentially life-saving indicator to support efficient and effective evacuations or to dispel the hazard. We propose a decentralized coordination method that allows multiple robots to efficiently sample and predict the behavior of environmental boundaries. Our method does not require a priori information about the boundary dynamics. We validate our proposal through experiments with actual robots. We demonstrate experimentally that our method can estimate and predict non-convex boundaries even with noisy measurements and inaccurate motion actuators.
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D. Saldaña, B. Gabrich, M. Whitzer, A. Prorok, M.F.M. Campos, M. Yim, and V. Kumar "A Decentralized Algorithm for Assembling Structures with Modular Robots"
IROS'2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems.

Abstract

Recent work in the field of bio-inspired robotic systems has introduced designs for modular robots that are able to assemble into structures (e.g., bridges, landing platforms, fences) using their bodies as the building components. Yet, it remains an open question as to how to program large swarms of robotic modules so that the assembly task is performed as efficiently as possible. Moreover, the problem of designing assembly algorithms is compounded by the scale of these systems, and by the lack of centralized guidance in unstructured environments. The main contribution of this work is a decentralized algorithm to assemble structures with modular robots. Importantly, we coordinate the robots so that docking actions can be parallelized. We show the correctness of our algorithm, and we demonstrate its scalability and generality through multiple scenarios in simulation. Experiments on physical robots demonstrate the validity of our approach in real-world settings.
Video

D. Saldaña, A. Prorok, S. Sundaram, M.F.M. Campos, and V. Kumar "Resilient Consensus for Time-Varying Networks of Dynamic Agents"
ACC'2017 - IEEE American Control Conference.

Abstract

We consider networks of dynamic agents that execute cooperative, distributed control algorithms in order to coordinate themselves and to collectively achieve goals. The agents rely on consensus algorithms that are based on local interactions with their nearest neighbors in the communication graph. However, such systems are not robust to one or more malicious agents and there are no performance guarantees when one or more agents do not cooperate. Recent results in network science deal with this problem by requiring specific graph topological properties. Nevertheless, the required network topologies imply high connectivity levels, which may be difficult to achieve in systems that exhibit time-varying communication graphs. In this paper, we propose an approach that provides resilience for networks of dynamic agents whose communication graphs are time-varying. We show that in the case where the required connectivity constraints cannot be satisfied at all times, we can resort to a consensus protocol that guarantees resilience when the union of communication graphs over a bounded period of time satisfies certain robustness properties. We propose a control policy to attain resilient behavior in the context of perimeter surveillance with a team of robots. We provide simulations that support our theoretical analyses.

A. Jahn, R. Javanmard Alitappeh, D. Saldaña, A.G. Santos, L. Pimenta, and M.F.M. Campos "Distributed Multi-Robot Coordination for Dynamic Perimeter Surveillance in Uncertain Environments"
ICRA'2017 - IEEE International Conference on Robotics and Automation.

Abstract

In perimeter surveillance, multiple robots circulate around the boundary of a desired region in order to create a virtual fence. The aim of the this fence is to avoid internal or external agents crossing through the delimited area. In this paper, we propose a distributed technique that allows a team of robots to plan the deformation of the boundary shape in order to escort the safe region from one place to a goal. Our proposal is composed of two parts. First, we present a distributed planning method for the dynamic boundary. We model the resulting plan as a twice differentiable function. Second, we use the obtained function to guide the robot team, where every member uses only local information for the controller. The robots distribute themselves along the time-varying perimeter and patrol around. We show in simulation how the robots behave in partially observable environments with static obstacles.

D. Saldaña, R. Javanmard Alitappeh, L. Pimenta, R. Assunção, and M.F.M. Campos "Dynamic Perimeter Surveillance with a Team of Robots"
ICRA'2016 - IEEE International Conference on Robotics and Automation.

Abstract

In this paper, we propose a motion planning method to escort a set of agents from one place to a goal in an environment with obstacles. The agents are distributed in a finite area, with a time-varying perimeter, in which we put multiple robots to patrol around it with a desired velocity. Our proposal is composed of two parts. The first one generates a plan to move and deform the perimeter smoothly, and as a result, we obtain a twice differentiable boundary function. The second part uses the boundary function to compute a trajectory for each robot, we obtain each resultant trajectory by first solving a differential equation. After receiving the boundary function, the robots do not need to communicate among themselves until they finish their trajectories. We validate our proposal with simulations and experiments with actual robots.
Video

D. Saldaña, R. Assunção, and M.F.M. Campos "A Distributed Multi-Robot Approach for the Detection and Tracking of Multiple Dynamic Anomalies"
ICRA'2015 - IEEE International Conference on Robotics and Automation.

Abstract

In many cases, large area disasters could be possibly be prevented if the incipient small-scale anomalies are detected in their early stages. A way to accomplish this would be to have multiple sensors deployed in disaster prone areas to detect anomalies. However, compared to static sensor networks, robotic sensor networks offer advantages such as active sensing, large area coverage and anomaly tracking. This paper addresses the problem of coordinating and controlling multiple robots for the detection of multiple dynamic anomalies in the environment. The main contribution of the work is a combined approach for the effective exploration under uncertainty, the anomaly tracking, and the autonomous on-line allocation of agents. Robots explore the work area maintaining the history of the sensed areas to reduce redundancy and to allow for full-map coverage. When an anomaly is detected, a robot autonomously determines how to either track the anomaly or to continue the exploration of the environment, depending on the size of the anomaly, which is estimated by the length of the perimeter of the enclosing polygon. We show results of our methodology both in simulation and with actual robots which have demonstrated that robots can autonomously and distributively be allocated to track or to explore depending on the behavior of the detected anomalies.

D. Saldaña, R. Melo, E. R. Nascimento, and M.F.M. Campos "Detecting Latent Variables of Interest in Geo-localized Environments Using an Aerial Robot"
LARS'2015 - 12th Latin American Robotics Symposium.

Abstract

In general, monitoring applications require human intervention whenever there is no physical sensors for the variables of interest (e.g. People in danger after a catastrophe). In this paper we describe an inference engine which is used to estimate latent variables that can not be perceived by sampling the physical phenomena directly. Our approach uses information from different types of sensors, and fuses them along with knowledge of experts. The inference engine works with probabilistic first order logic rules based on geo-located sensed data as evidences in order to dynamically create the structure of a Bayesian network. Our experiments, performed by using an aerial robot with a mounted RGB-Camera, show the capability of our method to detect people in danger situations, where the physical variables to being sensed are humans and fire.

D. Saldaña, L. Chaimowicz, and M.F.M. Campos "Searching and Tracking Anomalies with Multiple Robots: A Probabilistic Approach"
LARS'2014 - 11th Latin American Robotics Symposium.

Abstract

Real-time monitoring is paramount in environments where disasters may occur at any moment and when human or animal lives are in danger. Disasters usually are initiated by anomalies which were not timely detected and possibly corrected or even reported. In most cases it would be highly desirable to not only detect, but also to identify the affected area, whose perimeter may change over time. A typical example is the monitoring of a flammable forest, where the identification of increase in temperature, possibly due to fire is of utmost importance, but being able to determine the affected area in real time is also of great relevance to the firefighters. Similarly, detecting and tracking anomalies is an important task in several domains such as: oil spills in the water bodies, radiation leaks in nuclear power plants, and algae bloom in lakes.
Video

D. Saldaña, D. Ovalle, and A. Montoya "Improved algorithm for perimeter tracking in robotic sensor networks"
CLEI'2012 - XXXVIII Latin American informatics and computer science conference. , pp. 1-7..

D. Saldaña, D. Ovalle, and A. Montoya "A multi-agent model to control robotic sensor networks"
CCC'2012 - 7th Colombian Computing Conference.

D. Saldaña, D. Ovalle, and A. Montoya "MobSim: Una plataforma de desarrollo para Redes de Sensores Robóticas"
CCC'2011 - 6th Colombian Computing Conference.

D. Saldaña, D. Ovalle, and A. Montoya "Modelo Multi-Agente para la Coordinación de Preferencias de Usuarios en Ambientes Inteligentes"
CCC'2010 - 5th Colombian Computing Conference.

D. Saldaña, D. Ovalle, and A. Montoya "BlueContext: Sistema Multi-Agente para el Uso de Servicios Ubicuos a Través de Redes Bluetooth"
COMTEL'2010 - Congreso Internacional de Computación y Telecomunicaciones.

D. Saldaña, D. Ovalle, and A. Montoya "Building Ubuquitous Context-Sensitive Services Using Mobile Agents Through Wireless Networks"
LATINCOM'2009 - IEEE Latin-American Conference on Communications.

J. Atencio, C. Correa, D. Saldaña, and D. Aristizabal "Mecanismo para monitoreo de cultivos y agricultura de precisión usando redes de sensores inalámbricos"
2008 - Congreso Nacional de Ingeniería Agrícola y Áreas Afines..

Journals

D. Saldaña, P. M. Gupta, and V. Kumar "Design and Control of Aerial Modules for Inflight Self-disassembly"
RAL'2019 - IEEE Robotics and Automation Letters (2019).

Abstract

Robotic modular systems have the ability to create and break physical links to self-assemble larger custom robots for general tasks. In case of changes in the task or the environment, they can dynamically self-adapt by self-reconfigure during the mission. However, applying those concepts to flying vehicles is still a challenge. In this paper, we present a novel modular design based on a quadrotor platform that uses a lightweight passive mechanism to dock and undock in midair. Using this mechanism and a control strategy, we can divide a rectangular structure into two sub-structures during flight. The undocking action can be sequentially applied to disassemble structures into individual modules. Since self-assembly methods for aerial vehicles have been proposed in the literature, here we focus on the self-disassembly process. We validate our undocking method and self-disassembly algorithm through experiments with actual modules. We highlight that combining our proposed self-disassembly algorithm and existing self-assembly algorithms, aerial modules are able to perform inflight self-reconfiguration.
Video

L. Guerrero-Bonilla, D. Saldaña, and V. Kumar "Design guarantees for resilient robot formations on lattices"
RAL'2019 - IEEE Robotics and Automation Letters (2019).

Abstract

This paper presents guarantees to satisfy resilience on the communication network of robot formations. In these resilient networks, cooperative robots can achieve consensus in the presence of faulty or malicious robots. We propose a design framework on triangular and square lattices, providing an underlying structure for proximity-based robot networks. We present sufficient conditions on the robot communication range to guarantee resilient consensus. Our results can be used to design robot formations considering obstacles, number of robots, and energy usage. Additionally, robot networks with homogeneous and heterogeneous communication range are studied. We support our theoretical analysis with simulations on selected scenarios.

K. Saulnier, D. Saldaña, A. Prorok, G. Pappas, and V. Kumar "Resilient Flocking for Mobile Robot Teams"
RAL'2017 - IEEE Robotics and Automation Letters (July 2017).

Abstract

We present a method that enables resilient formation control for mobile robot teams in the presence of non-cooperative (defective or malicious) robots. Recent results in network science define graph topological properties that guarantee resilience against faults and attacks on individual nodes in static networks. We build on these results to propose a control policy that allows a team of mobile robots to achieve resilient consensus on the direction of motion. Our strategy relies on dynamic connectivity management that makes use of a metric that characterizes the robustness of the communication network topology. Our method distinguishes itself from prior work in that our connectivity management strategy ensures that the network lies above a critical resilience threshold, guaranteeing that our consensus algorithm always converges to a value within the convex hull of cooperative agents’ values. We demonstrate the use of our framework for resilient flocking, and show simulation results with groups of holonomic mobile robots.

D. Saldaña, R. Assunção, and M.F.M. Campos "Predicting Environmental Boundary Behaviors with a Mobile Robot"
RAL'2016 - IEEE Robotics and Automation Letters ( Volume: 1, Issue: 2, July 2016).

Abstract

Predicting the behavior of dangerous environmental boundaries, like spreading fire or oil spill, provides relevant information to mitigate the problem or even to support evacuation actions in order to save human or animal lives. In this letter, we present a model that uses a single robot moving around an environmental boundary in order to predict its shape by an analytical continuous function, which is based on the combination of polynomial approximation and Fourier Series. We show that the method converges to the exact boundary when we increase the sample frequency and the robot velocity. In order to evaluate the estimation quality, we performed experiments with simulated and actual robots. We applied our model in some dynamic boundaries presented in the literature, as in the application of plume-front estimation, showing that it accomplish accurate results.
Video

BookChapters

D. Saldaña, L. Guerrero-Bonilla, and V. Kumar "Resilient backbones in hexagonal robot formations"
DARS'2018 - Distributed Autonomous Robotic Systems: The 14th International Symposium. Springer International Publishing.

Abstract

Achieving consensus in distributed robot networks is a challenging task when the network contains non-cooperative robots. The conditions of robustness in communication networks are very restrictive and difficult to adapt to robot networks where the communication links are based on proximity. In this paper, we present a new topology network that is suitable for triangular lattices. We introduce sufficient conditions on hexagonal formations to offer resilience up to F non-cooperative robots. Using our framework, a resilient backbone can be designed to connect multiple points or to cover a given area while maintaining a robust communication network. We show theoretical guarantees for our proposed hexagonal formation and its variations. Different scenarios in simulations are presented to validate our approach.

D. Saldaña, A. Prorok, M.F.M. Campos, and V. Kumar "Triangular Networks for Resilient Formations"
DARS'2016 - Distributed Autonomous Robotic Systems: The 13th International Symposium. Springer International Publishing.

Abstract

Consensus algorithms allow multiple robots to achieve agreement on estimates of variables in a distributed manner, hereby coordinating the robots as a team,and enabling applications such as formation control and cooperative area coverage. These algorithms achieve agreement by relying only on local, nearest-neighbor communication. The problem with distributed consensus, however, is that a single malicious or faulty robot can control and manipulate the whole network. The objective of this paper is to propose a formation topology that is resilient to one malicious node, and that satisfies two important properties for distributed systems: (i) it can be constructed incrementally by adding one node at a time in such a way that the conditions for attachment can be computed locally, and (ii) its robustness can be verified through a distributed method by using only neighborhood-based information. Our topology is characterized by triangular robust graphs, consists of a modular structure, is fully scalable, and is well suited for applications of large-scale networks. We describe how our proposed topology can be used to deploy networks of robots. Results show how triangular robust networks guarantee asymptotic consensus in the face of a malicious agent.

D. Saldaña, L. Chaimowicz, and M.F.M. Campos "Searching for Regions Out of Normal Conditions Using a Team of Robots"
CCIS'2015 - Robotics. Communications in Computer and Information Science. Springer Berlin Heidelberg, 2015. 1-15..

Abstract

Searching for regions in abnormal conditions is a priority in environments susceptible to catastrophes (e.g. forest fires or oil spills). Those disasters usually begin with an small anomaly that may became unsustainable if it is not detected at an early stage. We propose a probabilistic technique to coordinate multiple robots in perimeter searching and tracking, which are fundamental tasks if they are to detect and follow anomalies in an environment. The proposed method is based on a particle filter technique, which uses multiple robots to fuse distributed sensor information and estimate the shape of an anomaly. Complementary sensor fusion is used to coordinate robot navigation and reduce detection time when an anomaly arises. Validation of our approach is obtained both in simulation and with real robots. Five different scenarios were designed to evaluate and compare the efficiency in both exploration and tracking tasks. The results have demonstrated that when compared to state-of-the art methods in the literature, the proposed method is able to search anomalies under uncertainty and reduce the detection time by automatically increasing the number of robots.
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