Guang Ling, Rovr Network - Decentralizing HD Maps for Autonomous Vehicles & AI (#51)
April 24, 2025 | 45:28 | Episode 51
In the race to build smarter cities and truly autonomous systems, accurate, large-scale, real-time 3D data. That’s exactly what Rovr Network is after.
In this episode of DePINed, host Tom Trowbridge welcomes Guang Ling, founder of Rovr, to unpack how his team is crowdsourcing the infrastructure needed to map the world — one lidar scan at a time. With years of experience in telecom and lidar systems, Ling is now leveraging the DePIN model to disrupt traditional 3D mapping and train the next generation of spatial AI.
What is Rovr?
Rovr is a DePIN protocol focused on collecting 3D street-level data through a distributed network of contributors. These contributors use either:
TX devices — low-cost hardware paired with a smartphone camera
LC devices — high-end units equipped with lidar, GNSS receivers, and IMUs
This data is used for two massive emerging markets:
HD maps for autonomous driving and advanced driver-assistance systems (ADAS)
3D training datasets for spatial AI and robotics
Unlike competitors that rely on a few expensive vehicles (think: Google’s $500K mapping cars), Rovr’s DePIN approach enables thousands of contributors to collect rich spatial data at a fraction of the cost.
The Perfect Storm for DePIN Mapping
According to Ling, this kind of project couldn’t have existed five years ago.
Three key factors aligned:
Hardware maturity — lidar and positioning sensors became dramatically cheaper.
Software maturity — open tools allow scalable data processing and aggregation.
Web3 incentive models — token economies can now reward data contributors effectively.
These advances made it finally possible to build a low-cost, high-fidelity, real-time mapping layer of the physical world, all powered by regular drivers.
“The lidar we’re using today is better than what Google used in their early mapping cars—and it’s much cheaper” — Guang Ling
The DePIN Model in Action
Rovr currently offers two tiers of hardware:
TX units (~$200): Already 3,000+ shipped. Use smartphone cameras to collect 2D data with GPS.
LC units (~$2,500): Include professional-grade lidar and sensors. First 50 shipping in early 2025.
Both systems feed data into Rovr’s growing spatial dataset. Contributors are rewarded using a points system, soon to be swapped for tokens post-TGE (planned for 2025). The reward logic is simple: more accurate, higher-quality, and more frequently updated data earns more points.
Expected payout:
TX: ~2 points/km
LC: ~20 points/km
The goal is to incentivize mapping of highway systems first, followed by urban areas starting in the U.S., Europe, Japan and South Korea.
Who Needs This Data?
The market for this data is huge and still largely underserved. Rovr is targeting:
Tier-1 ADAS providers (before going directly to OEMs)
AI companies training spatial models
Autonomous vehicle developers
AR/VR ecosystems needing real-world environments
Two massive market segments stand out:
HD Maps
Critical for autonomy. Today, HD maps cost ~$100/car/year from legacy vendors. Rovr aims to offer maps that are:
5x cheaper
12x more frequently updated (weekly vs. yearly)
“That’s ~60x more value for the customer,” Ling notes.
Spatial AI Data
While text, images, and audio are everywhere online, 3D datasets are rare, expensive, and hard to produce. Rovr enables collection of massive, high-resolution, real-world spatial data—fueling the next generation of LLMs, robotics, and AR agents.
Tokenomics & Revenue Flywheel
Rovr’s upcoming token model is designed to reinforce the utility loop:
Contributors earn tokens for collecting data.
Customers (ADAS providers, AI labs) pay Rovr for access.
80%+ of revenue will be used to buy and burn tokens, reducing supply and aligning long-term incentives.
Ling envisions building a token-sink economy, where the more data is used, the more value flows back to the network.
2025 Goals & Roadmap
By end of year, Rovr aims to reach:
1,000 LC devices and 5,000 TX devices active
100M km of 3D data collected
First millions in revenue, with active contracts from Tier-1 customers
TGE (token generation event) and point-to-token swap
Telecom Veteran → DePIN Builder
Guang Ling brings decades of experience to this challenge. He built over 2,000 telecom base stations in Asia, spent 7+ years at a top lidar company (supplying Google’s autonomous cars), and co-founded Pisces, a top Helium miner manufacturer.
The turning point? Seeing how Helium crowdsourced telecom infrastructure faster and cheaper than anyone thought possible.
“In 2011, it took us a full year, a thousand people, and millions of dollars to build 400 base stations. Helium did a million in a fraction of the time. That blew my mind.”
That realization led him to DePIN and now to Rovr.
The Bigger Picture
Rovr represents a shift in how infrastructure is deployed:
From centralized fleets → to decentralized contributors
From high cost → to low cost
From rare updates → to real-time streaming
In doing so, it aims to democratize access to spatial intelligence and lay the groundwork for autonomous systems and AI agents.
And in Ling’s words, this is just the beginning:
“Deep infrastructure is changing. DePIN is a deployment superpower”
About DePINed Podcast
DePINed is a podcast exploring the frontier of decentralized physical infrastructure, hosted by Tom Trowbridge, co-founder of Fluence. Each episode features in-depth conversations with founders, builders, and investors who are shaping the future of real-world Web3 networks.
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