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Distributed Data Fusion for Multirobot Search

IEEE TRANSACTIONS ON robotICS 2015年第1期31卷 55-66页

作者： Hollinger, Geoffrey A. Yerramalli, Srinivas Singh, Sanjiv Mitra, Urbashi Sukhatme, Gaurav S. Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97330 USA Qualcomm Res San Diego CA 92121 USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA Univ So Calif Ming Hsieh Dept Elect Engn Viterbi Sch Engn Los Angeles CA 90089 USA Univ So Calif Dept Comp Sci Viterbi Sch Engn Los Angeles CA 90089 USA

This paper presents novel data fusion methods that enable teams of vehicles to perform target search tasks without guaranteed communication. Techniques are introduced for merging estimates of a target's position from vehicles that regain contact after long periods of time, and a fully distributed team-planning algorithm is proposed, which utilizes limited shared information as it becomes available. The proposed data fusion techniques are shown to avoid overcounting information, which ensures that combining data from different vehicles will not decrease the performance of the search. Motivated by the underwater search domain, a realistic underwater acoustic communication channel is used to determine the probability of successful data transfer between two locations. The channel model is integrated into a simulation of multiple autonomous vehicles in both open water and harbor environments. The results demonstrate that the proposed distributed coordination techniques provide performance competitive with full communication.

关键词： Distributed robot systems marine robotics networked robots path planning for multiple mobile robot systems robotic search

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Adaptive Coordinating Construction of Truss Structures Using Distributed Equal-Mass Partitioning

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IEEE TRANSACTIONS ON robotICS 2014年第1期30卷 188-202页

作者： Yun, Seung-kook Rus, Daniela MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA

This paper presents a decentralized algorithm for the coordinated assembly of 3-D objects that consist of multiple types of parts, using a networked team of robots. We describe the algorithm and analyze its convergence and adaptation properties. We partition construction in two tasks: tool delivery and assembly. Each task is performed by a networked team of specialized robots. We analyze the performance of the algorithms using the balls into bins problem and show their adaptation to failure of robots, dynamic constraints, multiple types of elements, and re-configuration. We instantiate the algorithm to building truss-like objects using rods and connectors. We implement the algorithm in simulation and show results to construct 2-D and 3-D parts. Finally, we describe hardware implementation of the algorithms, where mobile manipulators assemble smart parts with IR beacons.

关键词： Distributed robot systems path planning for multiple mobile robot systems robotics in construction

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Point-Wise Fusion of Distributed Gaussian Process Experts (FuDGE) Using a Fully Decentralized robot Team Operating in Communication-Devoid Environment

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IEEE TRANSACTIONS ON robotICS 2018年第3期34卷 820-828页

作者： Tiwari, Kshitij Jeong, Sungmoon Chong, Nak Young Japan Adv Inst Sci & Technol Sch Informat Sci Nomi Ishikawa 9231292 Japan

In this paper, we focus on large-scale environment monitoring by utilizing a fully decentralized team of mobile robots. The robots utilize the resource constrained-decentralized active sensing scheme to select the most informative (uncertain) locations to observe while conserving allocated resources (battery, travel distance, etc.). We utilize a distributed Gaussian process (GP) framework to split the computational load over our fleet of robots. Since each robot is individually generating a model of the environment, there may be conflicting predictions for test locations. Thus, in this paper, we propose an algorithm for aggregating individual prediction models into a single globally consistent model that can be used to infer the overall spatial dynamics of the environment. To make a prediction at a previously unobserved location, we propose a novel gating network for a mixture-of-experts model wherein the weight of an expert is determined by the responsibility of the expert over the unvisited location. The benefit of posing our problem as a centralized fusion with a distributed GP computation approach is that the robots never communicate with each other, individually optimize their own GP models based on their respective observations, and off-load all their learnt models on the base station only at the end of their respective mission times. We demonstrate the effectiveness of our approach using publicly available datasets.

关键词： Distributed robot systems field robots model fusion path planning for multiple mobile robot systems surveillance systems

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planning and control for microassembly of structures composed of stress-engineered MEMS microrobots

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2013年第2期32卷 218-246页

作者： Donald, Bruce R. Levey, Christopher G. Paprotny, Igor Rus, Daniela Duke Univ Dept Comp Sci Durham NC 27708 USA Duke Univ Dept Biochem Med Ctr Durham NC 27708 USA Duke Univ Med Ctr Duke Inst Brain Sci Durham NC 27708 USA Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Univ Calif Berkeley Berkeley Sensor & Actuator Ctr Berkeley CA 94720 USA MIT Dept Elect Engn & Comp Sci Cambridge MA 02139 USA

We present control strategies that implement planar microassembly using groups of stress-engineered MEMS microrobots (MicroStressBots) controlled through a single global control signal. The global control signal couples the motion of the devices, causing the system to be highly underactuated. In order for the robots to assemble into arbitrary planar shapes despite the high degree of underactuation, it is desirable that each robot be independently maneuverable (independently controllable). To achieve independent control, we fabricated robots that behave (move) differently from one another in response to the same global control signal. We harnessed this differentiation to develop assembly control strategies, where the assembly goal is a desired geometric shape that can be obtained by connecting the chassis of individual robots. We derived and experimentally tested assembly plans that command some of the robots to make progress toward the goal, while other robots are constrained to remain in small circular trajectories (orbits) until it is their turn to move into the goal shape. Our control strategies were tested on systems of fabricated MicroStressBots. The robots are 240-280 mu m x 60 mu m x 7-20 mu m in size and move simultaneously within a single operating environment. We demonstrated the feasibility of our control scheme by accurately assembling five different types of planar microstructures.

关键词： micro/nano robots mechanics design and control path planning for multiple mobile robot systems mobile and distributed robotics MEMS underactuated robots

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An SMT-Based Approach to Motion planning for multiple robots With Complex Constraints

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IEEE TRANSACTIONS ON robotICS 2019年第3期35卷 669-684页

作者： Imeson, Frank Smith, Stephen L. Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

In this paper, we propose a new method for solving multirobot motion planning problems with complex constraints. We focus on an important class of problems that require an allocation of spatially distributed tasks to robots, along with efficient paths for each robot to visits their task locations. We introduce a framework for solving these problems that naturally couples allocation with path planning. The allocation problem is encoded as a Boolean Satisfiability problem (SAT) and the path planning problem is encoded as a traveling salesman problem (TSP). In addition, the framework can handle complex constraints such as battery life limitations, robot carrying capacities, and robot-task incompatibilities. We propose an algorithm that leverages recent advances in Satisfiability Modulo Theory (SMT) to combine state-of-the-art SAT and TSP solvers. We characterize the correctness of our algorithm and evaluate it in simulation on a series of patrolling, periodic routing, and multirobot sample collection problems. The results show our algorithm significantly outperforms state-of-the-art mathematical programming solvers.

关键词： Autonomous agents path planning for multiple mobile robot systems scheduling and coordination surveillance systems

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Detecting, localizing, and tracking an unknown number of moving targets using a team of mobile robots

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2017年第13-14期36卷 1540-1553页

作者： Dames, Philip Tokekar, Pratap Kumar, Vijay Temple Univ Dept Mech Engn Philadelphia PA 19122 USA Virginia Tech Dept Elect & Comp Engn Blacksburg VA USA Univ Penn Dept Mech Engn & Appl Mech Philadelphia PA 19104 USA

Target tracking is a fundamental problem in robotics research and has been the subject of detailed studies over the years. In this paper, we generate a data-driven target model from a real-world dataset of taxi motions. This model includes target motion, appearance, and disappearance from the search area. Using this target model, we introduce a new formulation of the mobile target tracking problem based on the mathematical concept of random finite sets. This formulation allows for tracking an unknown and dynamic number of mobile targets with a team of robots. We show how to employ the probability hypothesis density filter to simultaneously estimate the number of targets and their positions. Next, we present a greedy algorithm for assigning trajectories to the robots to allow them to actively track the targets. We prove that the greedy algorithm is a two-approximation for maximizing submodular tracking objective functions. We examine two such functions: the mutual information between the estimated target positions and future measurements from the robots and a new objective that maximizes the expected number of targets detected by the robot team. We provide extensive simulation evaluations to validate the performance of our data-driven motion model and to compare the behavior and tracking performance of robots using our objective functions.

关键词： Autonomous agents path planning for multiple mobile robot systems sensor fusion surveillance systems

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Multi-robot coverage and exploration on Riemannian manifolds with boundaries

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2014年第1期33卷 113-137页

作者： Bhattacharya, Subhrajit Ghrist, Robert Kumar, Vijay Univ Penn Dept Math Philadelphia PA 19104 USA Univ Penn Dept Mech Engn & Appl Mech Philadelphia PA 19104 USA

Multi-robot coverage and exploration are fundamental problems in robotics. A widely used, efficient and distributable algorithm for achieving coverage of a convex environment with Euclidean metrics is that proposed by Cortes which is based on the discrete-time Lloyd's algorithm. This algorithm is not directly applicable to general Riemannian manifolds with boundaries that are non-convex and are intrinsically non-Euclidean. In this paper we generalize the control law based on minimization of the coverage functional to such non-Euclidean spaces punctured by obstacles. We also propose a practical discrete implementation based on standard graph search-based algorithms. We demonstrate the applicability of the proposed algorithm by solving efficient coverage problems on a sphere and a torus with obstacles, and exploration problems in non-convex indoor environments.

关键词： Distributed robot systems mobile and distributed robotics SLAM path planning for multiple mobile robot systems autonomous agents cognitive robotics

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Algorithms for Cooperative Active Localization of Static Targets With mobile Bearing Sensors Under Communication Constraints

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IEEE TRANSACTIONS ON robotICS 2015年第4期31卷 864-876页

作者： Vander Hook, Joshua Tokekar, Pratap Isler, Volkan Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA

We study the problem of actively locating a static target using mobile robots equipped with bearing sensors. The goal is to reduce the uncertainty in the target's location to a value below a given threshold in minimum time. Our cost formulation explicitly models time spent in traveling, as well as taking measurements. In addition, we consider distance-based communication constraints between the robots. We provide the following theoretical results. First, we study the properties of an optimal offline strategy for one or more robots with access to the target's true location. We derive the optimal offline algorithm and bound its cost when considering a single robot or an even number of robots. In other cases, we provide a close approximation. Second, we provide a general method of converting the offline algorithm into an online adaptive algorithm (that does not have access to the target's true location), while preserving near optimality. Using these two results, we present an online strategy proven to locate the target up to a desired uncertainty level at near-optimal cost. In addition to theoretical analysis, we validate the algorithm in simulations and multiple field experiments performed using autonomous surface vehicles carrying radio antennas to localize radio tags.

关键词： Localization marine robotics networked robots path planning for multiple mobile robot systems

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Robust Cooperative Exploration With a Switching Strategy

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IEEE TRANSACTIONS ON robotICS 2012年第4期28卷 828-839页

作者： Wu, Wencen Zhang, Fumin Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

Biological inspirations have lead us to develop a switching strategy for a group of robotic sensing agents searching for a local minimum of an unknown noisy scalar field. Starting with individual exploration, the agents switch to cooperative exploration only when they are not able to converge to a local minimum at a satisfying rate. We derive a cooperative H-infinity filter that provides estimates of field values and field gradients during cooperative exploration and give sufficient conditions for the convergence and feasibility of the filter. The switched behavior from individual exploration to cooperative exploration results in faster convergence, which is rigorously justified by the Razumikhin theorem, to a local minimum. We propose that the switching condition from cooperative exploration to individual exploration is triggered by a significantly improved signal-to-noise ratio (SNR) during cooperative exploration. In addition to theoretical and simulation studies, we develop a multiagent testbed and implement the switching strategy in a lab environment. We have observed consistency of theoretical predictions and experimental results, which are robust to unknown noises and communication delays.

关键词： Cooperative exploration motion control path planning for multiple mobile robot systems sensor networks

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Capturing an evader in polygonal environments with obstacles: The full visibility case

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2012年第10期31卷 1176-1189页

作者： Bhadauria, Deepak Klein, Kyle Isler, Volkan Suri, Subhash Univ Calif Santa Barbara Dept Comp Sci Santa Barbara CA 93106 USA Univ Minnesota Dept Comp Sci Minneapolis MN 55455 USA

Suppose an unpredictable evader is free to move around in a polygonal environment of arbitrary complexity that is under full camera surveillance. How many pursuers, each with the same maximum speed as the evader, are necessary and sufficient to guarantee a successful capture of the evader? The pursuers always know the evader's current position through a camera network, but need to physically reach the evader to capture it. We allow the evader knowledge of the current positions of all the pursuers as well-this accords with the standard worst-case analysis model, but also models a practical situation where the evader has 'hacked' into the surveillance system. Our main result is to prove that three pursuers are always sufficient and sometimes necessary to capture the evader. The bound is independent of the number of vertices or holes in the polygonal environment.

关键词： path planning for multiple mobile robot systems mobile and distributed robotics SLAM sensor networks sensing and perception computer vision surveillance systems sensing and perception computer vision pursuit evasion games

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