Application of High-precision Timing Systems to Distributed Survey Systems

In any hydrographic survey system that consists of more than one computer, one of the most difficult integration problems is to ensure that all components maintain a coherent sense of time. Since virtually all modern survey systems are of this type, timekeeping and synchronized timestamping of data as it is created is of significant concern. This paper describes a method for resolving this problem based on the IEEE 1588 Precise Time Protocol (PTP) implemented by hardware devices, layered with some custom software called the Software Grandmaster (SWGM) algorithm. This combination of hardware and software maintains a coherent sense of time between multiple ethernet-connected computers, on the order of 100 ns (rms) in the best case, of the timebase established by the local GPS-receiver clock. We illustrate the performance of this techniques in a practical survey system using a Reson 7P sonar processor connected to a Reson 7125 Multibeam Echosounder (MBES), integrated with an Applanix POS/MV 320 V4 and a conventional data capture computer. Using the timing capabilities of the PTP hardware implementations, we show that the timepieces achieve mean (hardware based) synchronization and timestamping within 100-150 ns (rms), and that the data created at the Reson 7P without hardware timestamps has a latency variability of 28 µs (rms) due to software constraints within the capture system. This compares to 288 ms (rms) using Reson’s standard hybrid hardware/software solution, and 13.6 ms (rms) using a conventional single-oscillator timestamping model

A Distributed Pipeline for Scalable, Deconflicted Formation Flying

Reliance on external localization infrastructure and centralized coordination are main limiting factors for formation flying of vehicles in large numbers and in unprepared environments. While solutions using onboard localization address the dependency on external infrastructure, the associated coordination strategies typically lack collision avoidance and scalability. To address these shortcomings, we present a unified pipeline with onboard localization and a distributed, collision-free motion planning strategy that scales to a large number of vehicles. Since distributed collision avoidance strategies are known to result in gridlock, we also present a decentralized task assignment solution to deconflict vehicles. We experimentally validate our pipeline in simulation and hardware. The results show that our approach for solving the optimization problem associated with motion planning gives solutions within seconds in cases where general purpose solvers fail due to high complexity. In addition, our lightweight assignment strategy leads to successful and quicker formation convergence in 96-100% of all trials, whereas indefinite gridlocks occur without it for 33-50% of trials. By enabling large-scale, deconflicted coordination, this pipeline should help pave the way for anytime, anywhere deployment of aerial swarms.Comment: 8 main pages, 1 additional page, accepted to RA-L and IROS'2

Automatic Recognition of Object Use Based on Wireless Motion Sensors

In this paper, we present a method for automatic, online detection of a user’s interaction with objects. This represents an essential building block for improving the performance of distributed activity recognition systems. Our\ud method is based on correlating features extracted from motion sensors worn by the user and attached to objects. We present a complete implementation of the idea, using miniaturized wireless sensor nodes equipped with motion sensors. We achieve a recognition accuracy of 97% for a target response time of 2 seconds. The implementation is lightweight, with low communication bandwidth and processing needs. We illustrate the potential of the concept by means of an interactive multi-user game

Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved