Object transportation by multiple mobile robots controlled by attractor dynamics: theory and implementation

Dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for teams of mobile robots, that must transport a large object and simultaneously avoid collisions with (either static or dynamic) obstacles. Here we demonstrate in simulations and implementations in real robots that it is possible to simplify the architectures presented in previous work and to extend the approach to teams of n robots. The robots have no prior knowledge of the environment. The motion of each robot is controlled by a time series of asymptotical stable states. The attractor dynamics permits the integration of information from various sources in a graded manner. As a result, the robots show a strikingly smooth an stable team behaviour.

Using attractor dynamics to generate decentralized motion control of two mobile robots transporting a long object in coordination

Dynamical systems theory is used here as a theoretical language and tool to design a distributed control architecture for a team of two mobile robots that must transport a long object and simultaneously avoid obstacles. In this approach the level of modeling is at the level of behaviors. A “dynamics” of behavior is defined over a state space of behavioral variables (heading direction and path velocity). The environment is also modeled in these terms by representing task constraints as attractors (i.e. asymptotically stable states) or reppelers (i.e. unstable states) of behavioral dynamics. For each robot attractors and repellers are combined into a vector field that governs the behavior. The resulting dynamical systems that generate the behavior of the robots may be nonlinear. By design the systems are tuned so that the behavioral variables are always very close to one attractor. Thus the behavior of each robot is controled by a time series of asymptotically stable states. Computer simulations support the validity of our dynamic model architectures.

2D PCA-Based localization for mobile robots in unstructured environments

In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Anthropocentric-based robotic and autonomous systems: assessment for new organisational options

Text based on the paper presented at the Conference "Autonomous systems: inter-relations of technical and societal issues" held at Monte de Caparica (Portugal), Universidade Nova de Lisboa, November, 5th and 6th 2009 and organized by IET-Research Centre on Enterprise and Work Innovation

Vision based context categorization for all-terrain robot

Dissertation presented at the Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering.

Low cost inertial-based localization system for a service robot

Dissertation presented at Faculty of Sciences and Technology of the New University of Lisbon to attain the Master degree in Electrical and Computer Science Engineering

Autonomous bathymetry for risk assessment with ROAZ robotic surface vehicle

The use of unmanned marine robotic vehicles in bathymetric surveys is discussed. This paper presents recent results in autonomous bathymetric missions with the ROAZ autonomous surface vehicle. In particular, robotic surface vehicles such as ROAZ provide an efficient tool in risk assessment for shallow water environments and water land interface zones as the near surf zone in marine coast. ROAZ is an ocean capable catamaran for distinct oceanographic missions, and with the goal to fill the gap were other hydrographic surveys vehicles/systems are not compiled to operate, like very shallow water rivers and marine coastline surf zones. Therefore, the use of robotic systems for risk assessment is validated through several missions performed either in river scenario (in a very shallow water conditions) and in marine coastlines.

Swordfish: an Autonomous Surface Vehicle for Network Centric Operations

The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).

Marine Operations with the SWORDFISH Autonomous Surface Vehicle

IEEE Robótica 2007 - 7th Conference on Mobile Robots and Competitions, Paderne, Portugal 2007

Cascade Control of a Hexapod Robot

6th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, Catania, Italy, 17-19 September

Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

Multi-robot cooperative stereo for outdoor scenarios

13th International Conference on Autonomous Robot Systems (Robotica), 2013

Formation Control Driven by Cooperative Object Tracking

In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

Desenvolvimento e Controlo de um Veículo Autónomo Aéreo Quadrotor

A crescente necessidade de meios de inspecção e recolha de informação de infraestruturas e do meio ambiente natural, origina o recurso a meios tecnológicos cada vez mais evoluídos. Neste contexto, os robôs móveis autónomos aéreos surgem como uma ferramenta importante. Em particular, os veículos aéreos de asa móvel, pela sua manobrabilidade e controlo podem-se utilizar eficazmente em meios complexos como cenários interiores onde o ambiente é parcialmente controlado. A sua utilização em coordenação com outros veículos robóticos móveis e em particular com a crescente autonomia de decisão, permitem uma eficiência elevada, por exemplo, em tarefas de recolha automática de informação, vigilância, apoio a comunicações, etc. A inexistência de um veículo autónomo de asa móvel no cenário multi-robótico desenvolvido pelo Laboratório de Sistemas Autónomos do Instituto Superior de Engenharia do Porto, aliada às suas aplicações referidas, criou a necessidade do desenvolvimento de um veículo desta gama. Identificou-se, pois, o desenvolvimento de um veículo autónomo aéreo do tipo quadrotor com capacidade de vôo base estabilizado como o problema a resolver. Foi efectuado um levantamento de requisitos do sistema, a caracterização de um veículo autónomo aéreo Vertical Take-off and Landing - VTOL, e efectuado um trabalho de pesquisa a fim de possibilitar o conhecimento das técnicas e tecnologias envolvidas. Tendo em vista o objectivo de controlo e estabilização do veículo, foi efectuada a modelização do sistema que serviu não só para a melhor compreensão da sua dinâmica mas também para o desenvolvimento de um simulador que possibilitou a validação de estratégias de controlo e avaliação de comportamentos do veículo para diferentes cenários. A inexistência de controladores de motores brushless adequada (frequência de controlo), originou o desenvolvimento de um controlador dedicado para motores brushless, motores esses utilizados para a propulsão do veículo. Este controlador permite uma taxa de controlo a uma frequência de 20KHz, possui múltiplas interfaces de comunicação (CAN, RS232, Ethernet, SPI e JTAG), é de reduzido peso e dimensões e modular, visto ter sido implementado em dois módulos, i.e., permite a sua utilização com diferentes interfaces de potência. Projectou-se um veículo autónomo aéreo em termos físicos com a definição da sua arquitectura de hardware e software bem como o sistema de controlo de vôo. O sistema de estabilização de vôo compreende o processamento de informação fornecida por um sistema de navegação inercial, um sonar e o envio de referências de velocidade para cada um dos nós de controlo ligados a um barramento CAN instalado no veículo. A implementação do veículo foi alcançada nas suas vertentes mecânica, de hardware e software. O UAV foi equipado com um sistema computacional dotando-o de capacidades para o desempenho de tarefas previamente analisadas. No presente trabalho, são também tiradas algumas conclusões sobre o desenvolvimento do sistema e sua implementação bem como perspectivada a sua evolução futura no contexto de missões coordenadas de múltiplos veículos robóticos.