TICSync: Knowing when things happened

Abstract

Abstract-Modern robotic systems are composed of many distributed processes sharing a common communications infrastructure. High bandwidth sensor data is often collected on one computer and served to many consumers. It is vital that every device on the network agrees on how time is measured. If not, sensor data may be at best inconsistent and at worst useless. Typical clocks in consumer grade PCs are highly inaccurate and temperature sensitive. We argue that traditional approaches to clock synchronization, such as the use of NTP are inappropriate in the robotics context. We present an extremely efficient algorithm for learning the mapping between distributed clocks, which typically achieves better than millisecond accuracy within just a few seconds. We also give a probabilistic analysis providing an upper-bound error estimate.

Efficient Large‐scale Three‐dimensional Mobile Mapping for Underground Mines

“…Any noise, latencies, or errors in the timing directly contributes to errors in the point locations. There are techniques presented in the literature, such as TICSync (Harrison and Newman, ), that can efficiently and accurately estimate the latency of sensor measurements; however, it is just as important to dequantize, dejitter, or otherwise smooth the timestamps to ensure that they are clean and precise. The noise on the sampled system time has a standard deviation on the order of tens of milliseconds.…”

Continuous vehicle localisation using sparse 3D sensing, kernelised rényi distance and fast Gauss transforms

“…The laser is mounted on a vehicle and driven around a looping road. We take great care in synchronising the GPS/INS and 3D laser data streams using the TICSync algorithm [11]. We fit a Catmull-Rom spline (the details of which will be discussed in Section III-B) to the GPS/INS data.…”

Entropy-based sim(3) calibration of 2D lidars to egomotion sensors

“…jointly, we followed [7] and instead attempted to perform temporal calibration prior to spatial calibration, again through entropy minimization (instead of using, e.g., the TICSync library [27]). We locked the Sim(3) transform parameters at nominal values and varied the time delay t d between the camera and lidar data streams, performing a simple linear interpolation between camera poses.…”