Real-Time Localization Systems in Intralogistics: Empowering Manual Vehicles for the Mixed Fleet Era
Real-Time Localization Systems (RTLS) have become essential in modern intralogistics. Warehouses and factories are under pressure to boost efficiency, and RTLS provides the continuous visibility needed to optimize operations. As companies adopt more automated guided vehicles (AGVs) and autonomous mobile robots (AMRs), they realize that traditional manual vehicles – like forklifts and tugger trains – cannot be left behind. To achieve seamless mixed-fleet efficiency, even manually driven equipment must become “smart” and trackable in real time.
Increased automation doesn’t eliminate manual tasks; instead, it raises the stakes for coordination. A forklift without RTLS is essentially a blind spot in an otherwise connected environment, which can hinder the overall flow. In short, RTLS is the bridge between human-operated vehicles and intelligent automation, enabling all assets to work in unison toward higher productivity.
Problem Framing: The Challenge of Non-Tracked Manual Vehicles
In semi-automated warehouses, the absence of RTLS on manual vehicles creates significant challenges. Lack of visibility is a primary issue – if fleet managers cannot see a forklift’s live position, they cannot route around it or assign dynamic tasks efficiently. This leads to fragmented operations: AGVs may stop or slow down unnecessarily because they can’t predict the movements of nearby manual trucks, and human drivers are unaware of the paths planned for robots. The result is miscommunication and delays. For example, without a positioning system, an automated robot might encounter a manually driven forklift at an intersection and both will hesitate or stall, unsure who has right-of-way. Such uncoordinated interactions can even cause deadlocks or accidents in tight spaces.
Safety is another concern. Manual forklifts have accounted for numerous warehouse accidents in the past, and introducing robots doesn’t automatically solve this – in fact, it can complicate safety if robots aren’t aware of manned vehicles in real time. Collision avoidance systems work best when every moving asset is tracked. If manual drivers roam “invisible” to the automation system, you risk close calls or collisions where a robot might unexpectedly cross a forklift’s path.
Moreover, vehicles operate less efficiently when they aren’t synchronized. For instance, an automated tugger might wait at a transfer station because a manual pallet jack is unknowingly blocking the aisle ahead. With RTLS, these scenarios can be managed by smart traffic control (for example, triggering a traffic light or an alert) to coordinate passage. Without RTLS, such orchestration isn’t possible – the manual truck essentially operates in isolation.
There’s also a data gap. Companies today want to analyze fleet productivity, but if manual forklift movements aren’t logged, any optimization is based on guesswork. Where do forklifts spend most of their time? Which routes are congested? Without location data, these questions are hard to answer. A manual fleet lacking RTLS yields little to no accurate data on travel distances or idle times, meaning missed opportunities to improve throughput – for instance, eliminating unnecessary detours or balancing workloads among drivers.
Lastly, inventory accuracy suffers. An AGV automatically reports where it dropped a pallet, but a human driver might place a pallet in a convenient open spot and only later (if ever) record that location. Missing pallet locations and extra manual scanning are common pain points. RTLS can solve this by automatically logging where each load is picked and placed by a forklift, eliminating manual barcode scans and search time . In summary, when manual vehicles are not RTLS-equipped, companies face blind spots in coordination, safety risks, wasted efficiency, and data silos that undermine the promise of a semi-automated operation.
Comparing RTLS Technologies for Intralogistics
Multiple technologies can deliver real-time vehicle tracking in industrial settings. The main approaches include GPS, RFID, camera-based vision, UWB/BLE radio beacons, and LiDAR. Each has distinct infrastructure requirements and performance characteristics. Below we explore each option – looking at the needed infrastructure, real-time capabilities, precision, integration effort, scalability, and maturity – to see which is most suitable for enhancing intralogistics, especially for mixed fleets.
GPS
GPS relies on satellite signals, but those signals don’t penetrate buildings. That makes GPS mostly useless indoors. Even outdoors or in loading bays where you can get a fix, the accuracy tops out around 5–10 meters at best — barely enough to tell which aisle a vehicle is in. The upside is that it requires no onsite infrastructure; every forklift could carry a GPS receiver with no modifications to the facility. Unfortunately, inside a warehouse, GPS still leaves you with a huge blind spot.
RFID
Passive RFID tags can act like mile markers on the warehouse floor. Stick enough tags on the ground or racking, and a reader on the vehicle can identify specific spots — say, confirming a pallet was picked from the correct location. The tags themselves are cheap, but you’d need an extremely dense grid of them to track a vehicle continuously. In practice, RFID gives you a series of spot-checks rather than a live feed. Between tags, the truck is essentially invisible. Installing and maintaining all those tags is a major effort, so this approach is best for coarse tracking of key points rather than continuous positioning.
Camera SLAM
Camera-based localization comes in two flavors: onboard or external. An onboard camera can use SLAM (Simultaneous Localization and Mapping) to recognize surroundings and pinpoint the vehicle’s position with impressive accuracy — often within a few centimeters — without any fixed infrastructure. Alternatively, external cameras mounted on ceilings or walls can track vehicles visually from the outside. Vision provides rich context (for example, reading signs or detecting obstacles), but there are downsides. Performance is sensitive to lighting changes, glare, and occlusion (such as a dirty lens or a pallet blocking the view). Processing high-resolution video in real time also requires significant computing power. A dimly lit, dusty warehouse can quickly trip up a vision-based system.
Radio Beacon RTLS (UWB & BLE)
Ultra-wideband (UWB) and Bluetooth Low Energy (BLE) systems use radio beacons (anchors) around the facility to triangulate the position of a tag on each vehicle. UWB offers very high accuracy (around 10 cm) with rapid updates. BLE is cheaper and easier to deploy, but its accuracy is only a few meters unless you use advanced techniques like angle-of-arrival. One network of anchors can cover many vehicles at once, but installing and calibrating those anchors (or BLE beacons) is a project in itself. And because radio signals bounce off metal racks, BLE readings can sometimes jump around due to interference.
LiDAR
A 2D LiDAR scanner on the truck uses the warehouse’s own walls, racks, and other structures as landmarks to pinpoint the vehicle’s location. Precision is excellent — often on the order of 2–5 cm — and there’s no need to install any infrastructure; you just provide a digital map of the facility. LiDAR also works in conditions that would blind a camera, such as low light or airborne dust.
However, there are downsides. You’ll need a laser unit on each vehicle, and you must update the map whenever you rearrange the warehouse layout. Still, LiDAR often wins because it gives a manual truck the same centimeter-level awareness as an AMR, without peppering the facility with extra hardware. Drivers keep their freedom, and fleet managers get a continuous stream of reliable coordinates.
Future-Readiness: Importance of VDA 5050 Integration
Implementing RTLS is not just about immediate gains – it’s also an investment in future interoperability. One key consideration is to ensure that whatever tracking system you choose can plug into standardized, vendor-agnostic interfaces for fleet management. In intralogistics, VDA 5050 is emerging as an important standard. VDA 5050 (developed by German automotive and machinery industry associations) defines a universal communication protocol between a fleet management system and any automated vehicle (AGV/AMR), regardless of the manufacturer . In essence, it allows different brands of robots and vehicles to speak the same language to a central software controller.
Why does this matter for RTLS and manual vehicles? Because a manual vehicle equipped with an RTLS device can be treated in software as just another “vehicle” in the fleet. If your RTLS solution supports VDA 5050, then the live position and status of your manual forklifts can feed into a VDA 5050-compliant fleet manager alongside data from AGVs. The fleet manager doesn’t need to know or care that a certain unit is human-driven – it will receive its coordinates and telemetry in the same format as it gets from a robot.
This future-proofs your operation. For example, a traffic control system could automatically pause an AGV if a manual forklift (reporting via VDA 5050) is around the corner. Or it could dispatch the nearest available unit to a task regardless of vehicle type. Vendor-agnostic integration also avoids lock-in. You can mix and match equipment brands over time and still manage them under one umbrella, which is especially valuable in large facilities or as you upgrade piece by piece.
Supporting open standards like VDA 5050 ensures your RTLS investment will play nicely in the growing Industry 4.0 ecosystem, where multiple systems (WMS, MES, fleet software, etc.) need to share data. It’s the equivalent of making sure a new device can connect to the industrial “Internet of Things” out of the box. In sum, choosing RTLS technology that is compatible with standards (or at least offers open APIs while standards evolve) will enable seamless mixed-fleet coordination through unified interfaces, keeping your options open as automation scales up.
Conclusion
Implementing RTLS is not just about immediate gains – it’s also an investment in future interoperability. One key consideration is to ensure that whatever tracking system you choose can plug into standardized, vendor-agnostic interfaces for fleet management. In intralogistics, VDA 5050 is emerging as an important standard. VDA 5050 (developed by German automotive and machinery industry associations) defines a universal communication protocol between a fleet management system and any automated vehicle (AGV/AMR), regardless of the manufacturer . In essence, it allows different brands of robots and vehicles to speak the same language to a central software controller.
TL;DR
Manual and automated vehicles must work together: Even as warehouses deploy more AGVs and AMRs, most forklifts remain manual. RTLS (Real-Time Localization Systems) is crucial to integrate these human-driven vehicles into the connected, “smart” fleet.
Non-tracked forklifts cause blind spots: Without RTLS, manual vehicles become invisible in an automated environment, leading to coordination problems, delays (e.g. robots and forklifts hesitating at intersections), safety risks, and data gaps.
RTLS technologies vary: Solutions range from GPS (poor indoors), RFID tags (point checks only), camera SLAM (high precision but light-sensitive), UWB/BLE beacons (radio triangulation with varying accuracy), to vehicle-mounted LiDAR (centimeter-level precision with no infrastructure change). Each has pros and cons, but LiDAR-based localization often stands out for indoor use.
VDA 5050 standard for integration: Ensuring your RTLS supports standards like VDA 5050 helps future-proof the system. It allows manual forklifts with tracking to interface with fleet management software just like robots do, enabling unified traffic control and avoiding vendor lock-in.
Mixed fleets are here to stay: The vast majority of new forklifts are still manual.. Companies will operate mixed fleets for the long term, so upgrading manual equipment with RTLS yields significant benefits.
Benefits of RTLS on manual vehicles: Real-time tracking of forklifts and tugger trains improves safety (preventing collisions), boosts efficiency (optimized routes and reduced idle time), and can automate inventory updates (no manual barcode scans). Bringing manual vehicles into the digital loop ensures all assets – human-driven or autonomous – can work in sync, elevating overall productivity and safety in intralogistics.
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