Low-cost multi-robot exploration and mapping

Gifford, Chris; Webb, Russell Y.; J, Bley; Leung, Daniel; Calnon, M.; Makarewicz, Joseph; Banz, Bryan; Agah, Arvin

doi:10.1109/tepra.2008.4686676

Cited by 20 publications

(18 citation statements)

References 6 publications

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“…Although the full price of the robot is not reported, just the rotating sensor unit costs $390. Gifford et al [24] created an autonomous mapping robot using IR sensors. The reported price of each unit is $1, 250.…”

Section: Discussionmentioning

confidence: 99%

Simplified Occupancy Grid Indoor Mapping Optimized for Low-Cost Robots

Gonzalez-Arjona

Sanchez

López-Colino

et al. 2013

IJGI

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This paper presents a mapping system that is suitable for small mobile robots. An ad hoc algorithm for mapping based on the Occupancy Grid method has been developed. The algorithm includes some simplifications in order to be used with low-cost hardware resources. The proposed mapping system has been built in order to be completely autonomous and unassisted. The proposal has been tested with a mobile robot that uses infrared sensors to measure distances to obstacles and uses an ultrasonic beacon system for localization, besides wheel encoders. Finally, experimental results are presented.

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Section: Discussionmentioning

confidence: 99%

Simplified Occupancy Grid Indoor Mapping Optimized for Low-Cost Robots

Gonzalez-Arjona

Sanchez

López-Colino

et al. 2013

IJGI

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“…The procdure is similar. The landmark is first inserted in the state vector thanks to Equation (2). P is then augmented with an infinite variance for the landmark.…”

Section: Bias Integrationmentioning

confidence: 99%

“…We can cite: fast exploration [1] [2], localization without direct observation [3], risk as-sessment in dangerous situations [4], augmented reality for coordinated transportation [5], augmented reality for cellphones [6], improved localization accuracy [7], dense 3D reconstruction distributed over smartphones [8]... In the literature, multivehicle algorithms have been applied to field robotics [5], indoor environments [3], AUVs [9], UAVs [10] and heterogeneous teams [11].…”

Section: Introductionmentioning

confidence: 99%

A general consistent decentralized Simultaneous Localization And Mapping solution

Bresson

Aufrère

Chapuis

2015

Robotics and Autonomous Systems

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In this paper, we propose a new approach to the decentralized Simultaneous Localization And Mapping (SLAM) problem. The goal is to demonstrate the feasibility of decentralized localization using low-density maps built with low-cost sensors. This problem is challenging at different levels. Indeed, each vehicle localization tends to drift over time independently of one another making the global localization of a fleet hard to achieve. To counter this effect, called SLAM inconsistency and which has been stated numerous times in the literature, we introduce a model to represent the natural drift of SLAM algorithms. Its integration inside an Extended Kalman Filter is explained along with simulations validating its use. The second part of this paper presents the fusion architecture designed to solve the different problems arising in a decentralized scheme. It avoids data incest, which is an important source of inconsistency, and integrates the previously mentioned SLAM drift in the estimates produced. This architecture also separates the SLAM classically used for mono-vehicle applications from the high-level decentralized part offering flexibility regarding sensors and algorithms at a low-level. Other aspects, involved by the multi-vehicle settings, are also taken into account (communication losses, latencies, desynchronizations, unknown initial positions of the fleet members and data association). The whole algorithm has been tested in various scenarios with vehicles equipped with a single camera and an odometer. The results, from both simulated and real scenarios, show that our approach can work in real time with very small bandwidth requirements.

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“…They require at least laptop-level performances. Gifford et al [11] present a low-cost approach to autonomous multirobot mapping and exploration for unstructured environments. The robot hosts a Gumstix computing unit (600 Mhz), 6 IR scanning range arrays, a 3-axis gyroscope and odometers.…”

Section: Introductionmentioning

confidence: 99%

“…As pointed out by [11,12], the first improvement of a SLAM algorithm is an efficient setting of the various parameters of the algorithm. Other modifications were investigated to reach real-time constraints.…”

Section: Introductionmentioning

confidence: 99%

Real time simultaneous localization and mapping: towards low-cost multiprocessor embedded systems

Vincke

Elouardi

Lambert³

2012

J Embedded Systems

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Simultaneous localization and mapping (SLAM) is widely used by autonomous robots operating in unknown environments. Research community has developed numerous SLAM algorithms in the last 10 years. Several works have presented many algorithms' optimizations. However, they have not explored a system optimization from the system hardware architecture to the algorithmic development level. New computing technologies (SIMD coprocessors, DSP, multi-cores) can greatly accelerate the system processing but require rethinking the algorithm implementation. This article presents an efficient implementation of the EKF-SLAM algorithm on a multi-processor architecture. The algorithm-architecture adequacy aims to optimize the implementation of the SLAM algorithm on a low-cost and heterogeneous architecture (implementing an ARM processor with SIMD coprocessor and a DSP core). Experiments were conducted with an instrumented platform. Results aim to demonstrate that an optimized implementation of the algorithm, resulting from an optimization methodology, can help to design embedded systems implementing low-cost multiprocessor architecture operating under real-time constraints.

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Low-cost multi-robot exploration and mapping

Cited by 20 publications

References 6 publications

Simplified Occupancy Grid Indoor Mapping Optimized for Low-Cost Robots

Simplified Occupancy Grid Indoor Mapping Optimized for Low-Cost Robots

A general consistent decentralized Simultaneous Localization And Mapping solution

Real time simultaneous localization and mapping: towards low-cost multiprocessor embedded systems

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