Backend
Beyond Feasibility: Efficient and Robust On-Device Localization with UWB Concurrent Transmissions
arXiv cs.SY0 views
arXiv:2611.09619v1 Announce Type: cross Abstract: Concurrent transmissions (CTX) enable an ultra-wideband (UWB) tag to range to, or self-localize from, multiple nodes with a single frame reception, significantly improving update rate and energy efficiency compared to traditional approaches. Prior work demonstrated the concept feasibility via prototypes whose real-world applicability is however hindered by many limitations, notably including their inability to directly execute on UWB tags and to cope with interfering UWB signals. We address these limitations in two ways. First, we redesign the core CTX techniques to enable a fast and efficient execution on resource-constrained MCUs without sacrificing accuracy. Second, we leverage the new features in the IEEE 802.15.4z standard to achieve robustness to interference from other UWB devices and enable tags to dynamically select which anchors to use, two crucial and unexplored capabilities in CTX-based systems. We quantitatively evaluate our approach experimentally in two real-world testbeds with different characteristics. We first analyze our new techniques individually, offering an in-depth discussion of design choices and performance trade-offs. Then, we embed all our techniques into a CTX-based system enabling a tag to self-localize entirely on-device, unlocking gains up to 44% in runtime and 85% in energy efficiency compared to traditional approaches.
Source:https://arxiv.org/abs/2611.09619PreviousData-driven representation of continuous-time linear time-invariant behaviors via Hankel integral operatorsNextLACART: Lookahead-Augmented Collision Avoidance and Reference Tracking Strategies for Safety-Critical Robots
Related posts
Compiling a Custom Linux Kernel & Adding systemd (Part 2)
0dev.to
Git Things That Are Easy to Mess Up (Until They Bite You)
0dev.to
File System MCP Server: Scope Agent File Access Safely
0dev.to
NorSpeak: a free browser AI voice workbench (TTS, STT, live captions)
0dev.to
How AI Agents Pick Their Own Tools at Runtime (Without Hardcoding)
0dev.to
My On-Call Agent Stopped Suggesting the Fix That Failed
0dev.to