We consider the problem of reconfiguration planning in modular robots. Current techniques for reconfiguration planning usually specify the destination configuration for a modular robot explicitly. We posit that in unc...
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ISBN:
(纸本)9783642551468;9783642551451
We consider the problem of reconfiguration planning in modular robots. Current techniques for reconfiguration planning usually specify the destination configuration for a modular robot explicitly. We posit that in uncertain environments the desirable configuration for a modular robot is not known beforehand and has to be determined dynamically. In this paper, we consider this problem of how to identify a new 'best' configuration when a modular robot is unable to continue operating efficiently in its current configuration. We build on a technique that enumerates all the possible partitions of a set of modules requiring reconfiguring as a coalition structure graph (CSG) and finds the 'best' node in that graph. We propose a new data structure called an uncertain CSG (UCSG) that augments the CSG to handle uncertainty originating from the motion and performance of the robot. We then propose a new search algorithm called searchUCSG that intelligently prunes nodes from the UCSG using a modified branch and bound technique. Experimental results show that our algorithm is able to find a node that is within a worst bound of 80% of the optimal or best node in the UCSG while exploring only half the nodes in the UCSG. The time taken by our algorithm in terms of the number of nodes explored is also consistently lower than existing algorithms (that do not model uncertainty) for searching a CSG.
Applying coherent array processing to sound source localization when individual sensors are attached to heterogeneous platforms is a multi-faceted challenge for both perception and mobility. Recent technical advances ...
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ISBN:
(纸本)9783642551468;9783642551451
Applying coherent array processing to sound source localization when individual sensors are attached to heterogeneous platforms is a multi-faceted challenge for both perception and mobility. Recent technical advances in robot localization have made such mobile acoustic arrays possible, but the multi-robot coordination problem remains incomplete. How can a team of robots coordinate in cluttered environments, both with each other and static mounted sensors to effectively localize sound sources? This work proposes and implements a physicomimetics based robot control system with solid, liquid, and gas phase finite states. Applying these different phases appropriately enables efficient navigation through clutter and localization of both exposed and buried or hidden sound sources by teams of mobile robots.
In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights ...
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ISBN:
(纸本)9783642551468;9783642551451
In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights have associated deviation values that capture the non-determinism in the traveling times of the robot during its deployment. The mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied at the regions of the environment. Additionally, we have an optimizing proposition capturing some particular task that must be repeatedly completed by the team. The goal is to minimize the maximum time between successive satisfying instances of the optimizing proposition while guaranteeing that the mission is satisfied even under non-deterministic traveling times. After computing a set of optimal satisfying paths for the members of the team, we also compute a set of synchronization sequences for each robot to ensure that the LTL formula is never violated during deployment. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment.
In this paper we consider the problem of coordinating robotic systems with different kinematics, sensing and vision capabilities, to achieve certain mission goals. An approach that makes use of a heterogeneous team of...
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ISBN:
(纸本)9783642551468;9783642551451
In this paper we consider the problem of coordinating robotic systems with different kinematics, sensing and vision capabilities, to achieve certain mission goals. An approach that makes use of a heterogeneous team of agents has several advantages when cost, integration of capabilities, or possible large search areas need to be considered. A heterogeneous team allows for the robots to become "specialized", accomplish sub-goals more effectively, thus increasing the overall mission efficiency. We consider connectivity constraints and realistic communication, exploiting mobility to implement a power control algorithm that increases the Signal to Interference plus Noise Ratio (SINR) among certain members of the network. We also create realistic sensing fields and manipulation by using the geometric properties of the sensor field-of-view and the manipulability metric, respectively. The control strategy for each agent of the heterogeneous system is governed by an artificial physics law that considers the different kinematics of the agents and the environment, in a decentralized fashion. We show that the network is able to stay connected at all times and covers the environment well. We demonstrate the applicability of the proposed strategy through simulation results implementing a pursuit-evasion game in a cluttered environment.
This paper presents a novel approach to swarm navigation that combines hierarchical abstractions, flocking behaviors, and an efficient collision avoidance mechanism. Our main objective is to keep large groups of robot...
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ISBN:
(纸本)9783642551468;9783642551451
This paper presents a novel approach to swarm navigation that combines hierarchical abstractions, flocking behaviors, and an efficient collision avoidance mechanism. Our main objective is to keep large groups of robots segregated while safely navigating in a shared environment. For this, we propose the Virtual Group Velocity Obstacle, which is an extension of the Velocity Obstacle concept for groups of robots. By augmenting velocity obstacles with flocking behaviors and hierarchical abstractions, we are able to navigate robotic swarms in a cohesive and smooth fashion. A series of simulations and real experiments were performed and the results show the effectiveness of the proposed approach.
Flocking algorithms for a multi-agent system are distributed algorithms that only have simple rules for each agent but generate complex formational movement. These algorithms are known as swarm intelligence and are ro...
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ISBN:
(纸本)9783642551468;9783642551451
Flocking algorithms for a multi-agent system are distributed algorithms that only have simple rules for each agent but generate complex formational movement. These algorithms are known as swarm intelligence and are robust and disaster tolerant for most cases. We consider that flocking algorithms that have these characteristics are the way to generate homeostasis in a system. We expect that by making use of this algorithm the system can tune its self parameters and thus maintain a high performance. First, to apply a flocking algorithm to a system, we extended the flocking algorithm to form an arbitrary lattice for further flexibility. We then applied the extended flocking algorithm to a position tracking camera system as an example.
Emergent behavior in swarm robotic systems is key to obtaining complex behavior by a group of relatively simple agents. The question is how to design the individual behaviors of agents in such a way that the desired g...
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ISBN:
(纸本)9783642551468;9783642551451
Emergent behavior in swarm robotic systems is key to obtaining complex behavior by a group of relatively simple agents. The question is how to design the individual behaviors of agents in such a way that the desired global behavior emerges. Different approaches have been proposed to solve this problem: from biologically inspired probabilistic behavioral models to evolutionary techniques. In some situations, however, creating a complex probabilistic model of the behavior or developing a proper setup for an evolutionary process can be challenging. In this paper we propose a new method, based on supervised learning on a relatively small number of training samples. We apply our method to the well-known clustering problem and show that this approach yields the desired global clustering behavior.
This paper presents a nonlinear cyclic pursuit based target monitoring strategy for a group of autonomous vehicles. The vehicles are modeled as unicycles and are assumed to be heterogeneous. Each vehicle follows its n...
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ISBN:
(纸本)9783642551468;9783642551451
This paper presents a nonlinear cyclic pursuit based target monitoring strategy for a group of autonomous vehicles. The vehicles are modeled as unicycles and are assumed to be heterogeneous. Each vehicle follows its next neighbor as well as the target. Detailed analysis is done for a stationary target and the effectiveness of the proposed strategy with a moving target is shown in simulation. At equilibrium the vehicles capture the target and move along concentric circles in a rigid polygonal formation around the target with equal angular speeds. A necessary condition for the existence of equilibrium formation is derived. Local stability analysis is carried out for homogeneous agents. Simulation results illustrate the objective of the proposed method and demonstrates the derived results.
Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robo...
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ISBN:
(数字)9783319035932
ISBN:
(纸本)9783319035925;9783319035932
Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robot for field robotics, where collisions become an unavoidable part of the game. Theauthor argues that the design goal should be real anthropomorphism, as opposed to mere human-like appearance. He deduces three major characteristics to aim for when designing a humanoid robot, particularly robot hands:_ Robustness against impacts_ Fast dynamics_ Human-like grasping and manipulation performance Instead of blindly copying human anatomy, this book opts for a holistic design me-tho-do-lo-gy. It analyzes human hands and existing robot hands to elucidate the important functionalities that are the building blocks toward these necessary characteristics. They are the keys to designing an anthropomorphic robot hand, as illustrated in the high performance anthropomorphic Awiwi Hand presented in this book. This is not only a handbook for robot hand designers. It gives a comprehensive survey and analysis of the state of the art in robot hands as well as the human anatomy. It is also aimed at researchers and roboticists interested in the underlying functionalities of hands, grasping and manipulation. The methodology of functional abstraction is not limited to robot hands, it can also help realize a new generation of humanoid robots to accommodate a broader spectrum of the needs of human society.
The Human Hand as an Inspiration for Robot Hand Development presents an edited collection of authoritative contributions in the area of robot hands. The results described in the volume are expected to lead to more rob...
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ISBN:
(数字)9783319030173
ISBN:
(纸本)9783319030166
The Human Hand as an Inspiration for Robot Hand Development presents an edited collection of authoritative contributions in the area of robot hands. The results described in the volume are expected to lead to more robust, dependable, and inexpensive distributed systems such as those endowed with complex and advanced sensing, actuation, computation, and communication capabilities. The twenty-four chapters discuss the field of robotic grasping and manipulation viewed in light of the human hands capabilities and push the state-of-the-art in robot hand design and control. Topics discussed include human hand biomechanics, neural control, sensory feedback and perception, and robotic grasp and manipulation. This book will be useful for researchers from diverse areas such as robotics, biomechanics, neuroscience, and anthropologists.
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