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.

Culture, politics and identity: critical readings on gender in southeast Asia

Indian Journal of Gender Studies October 2012 vol. 19 no. 3 437-467

Coordinated transportation of a large object by a team of three robots

Dynamical systems theory in this work is used as a theoretical language and tool to design a distributed control architecture for a team of three robots that must transport a large object and simultaneously avoid collisions with either static or dynamic obstacles. The robots have no prior knowledge of the environment. The dynamics of behavior is defined over a state space of behavior variables, heading direction and path velocity. Task constraints are modeled as attractors (i.e. asymptotic stable states) of the behavioral dynamics. For each robot, these attractors are combined into a vector field that governs the behavior. By design the parameters are tuned so that the behavioral variables are always very close to the corresponding attractors. Thus the behavior of each robot is controlled by a time series of asymptotical stable states. Computer simulations support the validity of the dynamical model architecture.

Coordinated transportation of a large object by a team of two robots

In this paper dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for a team of two robots that must transport a large object and simultaneously avoid collisions with obstacles (either static or dynamic). This work extends the previous work with two robots (see [1] and [5]). However here we demonstrate that it’s possible to simplify the architecture presented in [1] and [5] and reach an equally stable global behavior. The robots have no prior knowledge of the environment. The dynamics of behavior is defined over a state space of behavior variables, heading direction and path velocity. Task constrains are modeled as attractors (i.e. asymptotic stable states) of a behavioral dynamics. For each robot, these attractors are combined into a vector field that governs the behavior. By design the parameters are tuned so that the behavioral variables are always very close to the corresponding attractors. Thus the behavior of each robot is controlled by a time series of asymptotic stable states. Computer simulations support the validity of the dynamical model architecture.

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.

Reconstrução de Superfícies usando um Scanner 3D de Luz Estruturada

Ao longo dos últimos anos, os scanners 3D têm tido uma utilização crescente nas mais variadas áreas. Desde a Medicina à Arqueologia, passando pelos vários tipos de indústria, ´e possível identificar aplicações destes sistemas. Essa crescente utilização deve-se, entre vários factores, ao aumento dos recursos computacionais, à simplicidade e `a diversidade das técnicas existentes, e `as vantagens dos scanners 3D comparativamente com outros sistemas. Estas vantagens são evidentes em áreas como a Medicina Forense, onde a fotografia, tradicionalmente utilizada para documentar objectos e provas, reduz a informação adquirida a duas dimensões. Apesar das vantagens associadas aos scanners 3D, um factor negativo é o preço elevado. No âmbito deste trabalho pretendeu-se desenvolver um scanner 3D de luz estruturada económico e eficaz, e um conjunto de algoritmos para o controlo do scanner, para a reconstrução de superfícies de estruturas analisadas, e para a validação dos resultados obtidos. O scanner 3D implementado ´e constituído por uma câmara e por um projector de vídeo ”off-the-shelf”, e por uma plataforma rotativa desenvolvida neste trabalho. A função da plataforma rotativa consiste em automatizar o scanner de modo a diminuir a interação dos utilizadores. Os algoritmos foram desenvolvidos recorrendo a pacotes de software open-source e a ferramentas gratuitas. O scanner 3D foi utilizado para adquirir informação 3D de um crânio, e o algoritmo para reconstrução de superfícies permitiu obter superfícies virtuais do crânio. Através do algoritmo de validação, as superfícies obtidas foram comparadas com uma superfície do mesmo crânio, obtida por tomografia computorizada (TC). O algoritmo de validação forneceu um mapa de distâncias entre regiões correspondentes nas duas superfícies, que permitiu quantificar a qualidade das superfícies obtidas. Com base no trabalho desenvolvido e nos resultados obtidos, é possível afirmar que foi criada uma base funcional para o varrimento de superfícies 3D de estruturas, apta para desenvolvimento futuro, mostrando que é possível obter alternativas aos métodos comerciais usando poucos recursos financeiros.