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IEEE International Conference on robotics and Automation (ICRA)

作者： M.A. Batalin G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Computer Science Department University of Southern California Los Angeles CA USA

In this paper we present the design and theoretical analysis of a novel algorithm (LRV) that efficiently solves the problems of coverage, exploration and sensor network deployment at the same time. The basic premise behind the algorithm is that the robot carries network nodes as a payload, and in the process of moving around, emplaces the nodes into the environment based on certain local criteria. In turn, the nodes emit navigation directions for the robot as it goes by. Nodes recommend directions least recently visited by the robot, hence the name LRV. We formally establish the following two properties: 1. LRV is complete on graphs, and 2. LRV is optimal on trees. We present some experimental conjectures for LRV on regular square lattice graphs and compare its performance empirically to other graph exploration algorithms.

关键词： Algorithm design and analysis Robot sensing systems Sensor systems embedded system Payloads Navigation Laboratories Computer science Tree graphs Lattices

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Towards geometric 3D mapping of outdoor environments using mobile robots

Towards geometric 3D mapping of outdoor environments using m...

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2005 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： D. Wolf A. Howard G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

This paper presents an approach to generating compact 3D maps of urban environments using mobile robots and laser range finders. Our algorithm extracts planar information from 3D point cloud maps. The planar representation is very efficient for representing building structures in urban environments when a high level of detail is not required. We also present preliminary results on 3D geometric mapping with incomplete data. Based on previously known models and incomplete data, our system is able to estimate parts of buildings which have never been seen before. As validation, we present experimental results using a Segway RMP vehicle in two environments, both approximately the size of a city block.

关键词： Mobile robots Terrain mapping Vehicles Indoor environments embedded system Data mining Clouds Buildings Robot sensing systems Data acquisition

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Using a sensor network for distributed multi-robot task allocation

Using a sensor network for distributed multi-robot task allo...

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.A. Batalin G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Computer Science Department University of Southern California Los Angeles CA USA

We present a multi field distributed in-network task allocation (DINTA-MF) algorithm for online multi-robot task allocation (OMRTA) where tasks are allocated explicitly to robots by a pre-deployed, static sensor network. The idea of DINTA-MF is to compute several assignment fields in the sensor network and then distributively assign fields to different robots. Experimental results with a simulated alarm scenario show that our approach is able to compute solutions to the OMRTA problem in a distributed fashion and arguably in an optimal way. We compared DINTA-MF with a simpler implementation (DINTA), which uses one assignment field. The data show that DINTA-MF outperforms DINTA as the number of robots increases.

关键词： Robot sensing systems Navigation Computer networks Mobile robots embedded system Distributed computing Wireless sensor networks Laboratories Computer science Sensor systems

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Constrained coverage for mobile sensor networks

Constrained coverage for mobile sensor networks

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IEEE International Conference on robotics and Automation (ICRA)

作者： S. Poduri G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

We consider the problem of self-deployment of a mobile sensor network. We are interested in a deployment strategy that maximizes the area coverage of the network with the constraint that each of the nodes has at least K neighbors, where K is a user-specified parameter. We propose an algorithm based on artificial potential fields which is distributed, scalable and does not require a prior map of the environment. Simulations establish that the resulting networks have the required degree with a high probability, are well connected and achieve good coverage. We present analytical results for the coverage achievable by uniform random and symmetrically tiled network configurations and use these to evaluate the performance of our algorithm.

关键词： Mobile robots Sensor systems Robot sensing systems embedded system Taxonomy Laboratories Computer science Mobile computing Global Positioning System Fires

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Efficient exploration without localization

Efficient exploration without localization

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.A. Batalin G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Computer Science Department University of Southern California Los Angeles CA USA Center for Robotics and Embedded Systems University of Southern California Los Angeles CA USA

We study the problem of exploring an unknown environment using a single robot. The environment is large enough (and possibly dynamic) that constant motion by the robot is needed to cover the environment. We term this the dynamic coverage problem. We present an efficient minimalist algorithm which assumes that global information is not available to the robot (neither a map, nor GPS). Our algorithm uses markers which the robot drops off as signposts to aid exploration. We conjecture that our algorithm has a cover time better than O(n log n), where the n markers that are deployed form the vertices of a regular graph. We provide experimental evidence in support of this conjecture. We show empirically that the performance of our algorithm on graphs is similar to its performance in simulation.

关键词： Robot sensing systems embedded system Orbital robotics Computer science Global Positioning System Target tracking Monitoring Security Buildings Earthquakes

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Mobile robot navigation using a sensor network

Mobile robot navigation using a sensor network

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.A. Batalin G.S. Sukhatme M. Hattig Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Computer Science Department University of Southern California Los Angeles CA USA Open Source Robotics Intel Corporation Hillsboro OR USA

We describe an algorithm for robot navigation using a sensor network embedded in the environment. Sensor nodes act as signposts for the robot to follow, thus obviating the need for a map or localization on the part of the robot. Navigation directions are computed within the network (not on the robot) using value iteration. Using small low-power radios, the robot communicates with nodes in the network locally, and makes navigation decisions based on which node it is near. An algorithm based on processing of radio signal strength data was developed so the robot could successfully decide which node neighborhood it belonged to. Extensive experiments with a robot and a sensor network confirm the validity of the approach.

关键词： Mobile robots Robot sensing systems Orbital robotics Radio navigation embedded system Sensor phenomena and characterization Computer networks Motion planning State-space methods Mobile communication

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Combined optic-flow and stereo-based navigation of urban canyons for a UAV

Combined optic-flow and stereo-based navigation of urban can...

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作者： Hrabar, Stefan Sukhatme, Gaurav S. Corke, Peter Usher, Kane Roberts, Jonathan Robotic Embedded Systems Laboratory University of Southern California Los Angeles CA United States CSIRO ICT Center P.O. Box 883 Kenmore 4069 QLD Australia

ISBN: (纸本)0780389123

We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front. The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereoflow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images. © 2005 IEEE.

关键词： Stereo image processing

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Distilling motion planner augmented policies into visual control policies for robot manipulation

arXiv

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arXiv 2021年

作者： Liu, I-Chun Arthur Uppal, Shagun Sukhatme, Gaurav S. Lim, Joseph J. Englert, Peter Lee, Youngwoon Cognitive Learning for Vision and Robotics Lab University of Southern California Robotic Embedded Systems Laboratory University of Southern California

Learning complex manipulation tasks in realistic, obstructed environments is a challenging problem due to hard exploration in the presence of obstacles and high-dimensional visual observations. Prior work tackles the exploration problem by integrating motion planning and reinforcement learning. However, the motion planner augmented policy requires access to state information, which is often not available in the real-world settings. To this end, we propose to distill a state-based motion planner augmented policy to a visual control policy via (1) visual behavioral cloning to remove the motion planner dependency along with its jittery motion, and (2) vision-based reinforcement learning with the guidance of the smoothed trajectories from the behavioral cloning agent. We evaluate our method on three manipulation tasks in obstructed environments and compare it against various reinforcement learning and imitation learning baselines. The results demonstrate that our framework is highly sample-efficient and outperforms the state-of-the-art algorithms. Moreover, coupled with domain randomization, our policy is capable of zero-shot transfer to unseen environment settings with distractors. Code and videos are available at https://***/mopa-pd. © 2021, CC BY.

关键词： Motion planning

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A visual servoing approach for tracking features in urban areas using an autonomous helicopter

A visual servoing approach for tracking features in urban ar...

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IEEE International Conference on robotics and Automation (ICRA)

作者： L. Mejias P. Campoy S. Saripalli G.S. Sukhatme Computer Vision Group Universidad Politécnica de Madrid Madrid Spain Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

The use of unmanned aerial vehicles (UAVs) in civilian and domestic applications is highly demanding, requiring a high-level of capability from the vehicles. This work addresses the design and implementation of a vision-based feature tracker for an autonomous helicopter. Using vision in the control loop allows estimating the position and velocity of a set of features with respect to the helicopter. The helicopter is then autonomously guided to track these features (in this case windows in an urban environment) in real time. The results obtained from flight trials in a real world scenario demonstrate that the algorithm for tracking features in an urban environment, used for visual servoing of an autonomous helicopter is reliable and robust

关键词： Visual servoing Urban areas Helicopters Aircraft navigation Machine vision Control systems Unmanned aerial vehicles Global Positioning System Computer vision Robot vision systems

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Robomote: a tiny mobile robot platform for large-scale ad-hoc sensor networks

Robomote: a tiny mobile robot platform for large-scale ad-ho...

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IEEE International Conference on robotics and Automation (ICRA)

作者： G.T. Sibley M.H. Rahimi G.S. Sukhatme Robotic Embedded Systems Laboratory Robotics Research Laboratory Department of Computer Science University of Southern California Los Angeles CA USA

This paper introduces Robomote, a robotic solution developed to explore problems in large-scale distributed robotics and sensor networks. The design explicitly aims at enabling research in sensor networking, adhoc networking, massively distributed robotics, and extended longevity. The platform must meet many demanding criteria not limited to but including: miniature size, low power, low cost, simple fabrication, and a sensor/actuator suite that facilitates navigation and localization. We argue that a robot test bed such as Robomote is necessary for practical research with large networks of mobile robots. Further, we present a preliminary analysis of Robomotes' success to this end.

关键词： Mobile robots Large-scale systems Robot sensing systems Costs Orbital robotics Laboratories Actuators Humans Sensor systems Navigation

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