Solution

LiDAR solution for UAV detection and avoidance

Provide forward or downward range input so the UAV system can trigger slowdown, rerouting, or stop logic.

UAV using LiDAR to detect forward obstacles

Scenario

Application scenario

LiDAR outputs target range and status; obstacle classification, risk decisions, path planning, and actuation remain with the flight controller or companion computer.

Engineering problem

Obstacle height, material, and incidence angle vary.
Multi-direction mounting requires separate calibration and blind-zone handling.
Avoidance thresholds, redundancy, and safety policy belong to the vehicle system.

Why LiDAR

Direct range input is straightforward to connect to threshold, slowdown, and stop logic, but it must be validated on the target aircraft.

Workflow

Define detection direction, targets, minimum clearance, and actions.
Select a model by range, field of view, and mounting space.
Connect range, status, and timestamps to the flight controller or companion computer.
Validate false positives, misses, and fallback with real obstacles and flight speeds.

Technology comparison and selection

Dimension	Condition	LiDAR	Alternative	Alternative performance	Conclusion
Obstacle range input	The system needs an explainable distance threshold and action trigger.	Range and status from a point measurement.	Vision-based avoidance	Provides shape information but depends on light, models, and compute.	Combine both where needed; LiDAR does not replace classification or planning. 公开来源Benewake customer application materials · Verified 2026-09-01

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Selection

Product selection guide

Current material supports 4 candidates. Review product facts, rationale and boundaries together.

Model	Key product facts	Best fit and rationale	Operating boundary	Product details
TFmini-S	Output data Single-point Distance Value Measuring range 0.1 ~ 12 m Interface UART, I/O, I²C Protection 未注明	For short-range, single-direction obstacle distance input when payload is constrained, such as low-speed or local-direction sensing.	One distance point does not provide complete avoidance coverage; combine it with flight speed, stopping distance, blind-zone and redundant-sensing design.	View product
TFS20-L	Output data Single-point Distance Value Measuring range 0.2 ~ 20 m Interface UART, I²C Protection Without enclosure	For directional detection on ultra-light platforms needing a 20 m-class forward range input.	It is unenclosed and single-point; flight tests must cover low-reflectivity targets, strong light, attitude change and control reaction time.	View product
TFA170-L	Output data Single-point Distance Value Measuring range 0.1 ~ 170 m Interface RS-232 Protection Without enclosure	For long-range warning input on payload-constrained UAVs, providing distance in a defined direction.	An unenclosed narrow-field RS-232 sensor is not omnidirectional avoidance; validate target size, optical alignment and maneuver margin.	View product
TF03	Output data Single-point Distance Value Measuring range 0.1 ~ 180 m Interface UART, CAN, RS-232, RS-485 Protection IP67	For directional detection where the platform can carry more weight and needs long range, IP67 and multiple interfaces.	Do not convert specified range directly into avoidance distance; validate coverage, target, background, speed, stopping and failure strategy at system level.	View product

Continue with a relevant model-difference topic

Balancing range, weight and environment at long distance

Installation and integration

Rigidly mount for the detection direction and record attitude; handle range status, thresholds, and fallback in the flight controller or companion computer.
TF02-Pro / TF03 / TFmini-S · Flight controller, companion computer, or UAV safety system · Target system release to be verified before deploymentBenewake customer application materials · Verified 2026-09-01

Operating limits

LiDAR does not classify obstacles or plan paths; out-of-range, occlusion, low-reflectivity, and fast-moving targets require separate validation.
TF02-Pro / TF03 / TFmini-SBenewake customer application materials · Verified 2026-09-01

Evidence

Research, ecosystem and customer stories

TFmini-S and TF-NOVA in honeybee-inspired navigation research

Institution: Delft University of Technology, Micro Air Vehicle Laboratory
Model: —
Use: The paper records TFmini-S and TF-NOVA model use in robot-navigation experiments.
Provenance: Efficient robot navigation inspired by honeybee learning flights 2026 DOI: 10.1038/s41586-026-10461-3
Attribution: Model-level: model named in the source

Open original source ↗View evidence citation →

FAQ

Frequently asked questions

Does the Benewake product perform avoidance by itself?

The product provides range and status. Obstacle decisions, counting, slowdown, rerouting, and stop actions are implemented by the customer flight stack or upper system.

Resources

Resources and references

DatasheetTF02-Pro Datasheet
DatasheetTF03 Series Datasheet

Confirm the selection with real mission conditions

Share the operating height, target surface, environment, mounting space, and flight-stack version. Our engineering team can help plan selection and validation.

Talk to an engineer