2,177 research outputs found
Robot control with biological cells
At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robot’s actuators
Control of synchronization regimes in networks of mobile interacting agents
We investigate synchronization in a population of mobile pulse-coupled agents with a view towards
implementations in swarm robotics systems and mobile sensor networks. Previous theoretical
approaches dealt with range and nearest neighbor interactions. In the latter case, a synchronization-hindering
regime for intermediate agent mobility was found. In the present work, we investigate
the robustness of this intermediate regime under practical scenarios. We show that synchronization
in the intermediate regime can be predicted by means of a suitable metric of the phase response
curve. Furthermore, we study more realistic K-nearest neighbors and cone of vision interactions,
showing that it is possible to control the extent of the synchronization-hindering region by appropriately
tuning the size of the neighborhood. To assess the effect of noise, we analyze the
propagation of perturbations over the network and draw an analogy between the response in the
hindering regime and stable chaos. Our findings reveal the conditions for the control of clock or
activity synchronization of agents with intermediate mobility. In addition, the emergence of the
intermediate regime is validated experimentally using a swarm of physical robots interacting with
cone of vision interactions
Timed trajectory generation combined with an Extended Kalman Filter for a vision-based autonomous mobile robot
Series : Advances in intelligent systems and computing, vol. 193, ISSN 2194-5357Planning collision-free trajectories requires the combination of generation and modulation techniques. This is especially important if temporal stabilization of the generated trajectories is considered. Temporal stabilization means to conform to the planned movement time, in spite of environmental conditions or perturbations. This timing problem has not been addressed in most current robotic systems, and it is critical in several robotic tasks such as sequentially structured actions or human-robot interaction. This work focuses on generating trajectories for a mobile robot, whose goal is to reach a target within a constant time, independently of the world complexity. Trajectories are generated by nonlinear dynamical systems. Herein, we extend our previous work by including an Extended Kalman Filter (EKF) to estimate the target location relative to the robot. A simulated hospital environment and a Pioneer 3-AT robot are used to demonstrate the robustness and reliability of the proposed approach in cluttered, dynamic and uncontrolled scenarios. Multiple experiments confirm that the inclusion of the EKF preserves the timing properties of the overall architecture.Work supported by the Portuguese Science Foundation (grant PTDC/EEA-CRO/100655/2008), and by project FCT PEst-OE/EEI/LA0009/2011. Jorge B. Silva is supported by PhD Grant SFRH/BD/68805/2010, granted by the Portuguese Science Foundation
Synchronization in dynamical networks of locally coupled self-propelled oscillators
Systems of mobile physical entities exchanging information with their
neighborhood can be found in many different situations. The understanding of
their emergent cooperative behaviour has become an important issue across
disciplines, requiring a general conceptual framework in order to harvest the
potential of these systems. We study the synchronization of coupled oscillators
in time-evolving networks defined by the positions of self-propelled agents
interacting in real space. In order to understand the impact of mobility in the
synchronization process on general grounds, we introduce a simple model of
self-propelled hard disks performing persistent random walks in 2 space and
carrying an internal Kuramoto phase oscillator. For non-interacting particles,
self-propulsion accelerates synchronization. The competition between agent
mobility and excluded volume interactions gives rise to a richer scenario,
leading to an optimal self-propulsion speed. We identify two extreme dynamic
regimes where synchronization can be understood from theoretical
considerations. A systematic analysis of our model quantifies the departure
from the latter ideal situations and characterizes the different mechanisms
leading the evolution of the system. We show that the synchronization of
locally coupled mobile oscillators generically proceeds through coarsening
verifying dynamic scaling and sharing strong similarities with the phase
ordering dynamics of the 2 XY model following a quench. Our results shed
light into the generic mechanisms leading the synchronization of mobile agents,
providing a efficient way to understand more complex or specific situations
involving time-dependent networks where synchronization, mobility and excluded
volume are at play
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