Abstract-Recent multi-robot exploration algorithms usually rely on occupancy grids as their core world representation. However, those grids are not appropriate for environments that are very large or whose boundaries are not well delimited from the beginning of the exploration. In contrast, polygonal representations do not have such limitations. Previously, the authors have proposed a new exploration algorithm based on partitioning unknown space into as many regions as available robots by applying K-Means clustering to an occupancy grid representation, and have shown that this approach leads to higher robot dispersion than other approaches, which is potentially beneficial for quick coverage of wide areas. In this paper, the original K-Means clustering applied over grid cells, which is the most expensive stage of the aforementioned exploration algorithm, is substituted for a Voronoi-based partitioning algorithm applied to polygons. The computational cost of the exploration algorithm is thus significantly reduced for large maps. An empirical evaluation and comparison of both partitioning approaches is presented.
The inverted pendulum is a non-linear unbalanced system that needs to be controlled using motors to achieve stability and equilibrium. The inverted pendulum is constructed with Lego and using the Lego Mindstorm NXT, which is a programmable robot capable of completing many different functions. In this paper, an initial design of the inverted pendulum is proposed and the performance of different sensors, which are compatible with the Lego Mindstorm NXT was studied. Furthermore, the ability of computer vision to achieve the stability required to maintain the system is also investigated. The inverted pendulum is a conventional cart which can be controlled using a Fuzzy Logic controller that produces a self-tuning PID control for the cart to move on. The fuzzy logic and PID are simulated in MATLAB and Simulink, and the program for the robot developed in the LabVIEW software.
Abstract-This paper reviews the state of the art in coordinated multi-robot exploration and proposes a new exploration objective based on a practical scenery, reducing the difference of waiting time among different regions of a workspace, which has not been still considered in the literature. A new global optimization strategy for coordinated multi-robot exploration based on a proper dispersion of robots in separate regions is presented. This strategy aims at achieving the lowest variance of regional waiting time and the lowest variance of regional exploration percentage. Both features reveal that the proposed strategy performs better than other state of the art approaches.
The objective of this paper is to describe an approach to detect the slip and contact force in real-time feedback. In this novel approach DAVIS camera used as a vision tactile sensor due to its fast process speed and high resolution. Two hundred experiments were performed on four objects with different shape, size, weight and material to compare the accuracy and respond of the Baxter robot grippers to avoid slipping. The advanced approach is validated by using a force-sensitive resistor (FSR402). The events captured with DAVIS camera are processed with specific algorithms to provide feedback to the Baxter robot aiding it to detect the slip.
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