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Perception Processing for Robotics: Pose, Depth and 3D Mesh cover
AI & MLGeospatialManufacturing Kuinbee reviewed
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Fenon Robotics

Perception Processing for Robotics: Pose, Depth and 3D Mesh

Convert camera and sensor captures into calibrated pose tracks, depth products, spatial reconstructions, and 3D meshes for robotics and physical AI training pipelines.

Typical turnaround: 2–21 days

About this service

Fenon Robotics provides the perception layer that converts raw physical-world captures into structured, training-ready representations for robotics and physical AI models. The service processes stereo, monocular, mobile, UMI, VR, and synchronized sensor inputs to produce human and hand pose tracks, camera trajectories, depth maps, point clouds, object and workspace geometry, and 3D meshes. Pipelines can be configured for offline datasets or integrated into a recurring ingestion workflow, with outputs aligned to the buyer's model architecture, coordinate conventions, frame rate, and quality thresholds. This service can be paired with Fenon's India-wide field operations or applied to buyer-supplied captures. It is designed for manipulation, embodied perception, navigation, teleoperation, scene understanding, and simulation or digital-twin preparation across manufacturing, logistics, agriculture, jewellery, textiles, and other real-world domains. Perception infrastructure is usage-based and billed per second of processed compute rather than through reserved capacity blocks. A representative pilot establishes the appropriate pipeline, accuracy checks, throughput, and unit economics before production scale-up.

Collection methods

Api integrationImage and video captureOffline and recurring perception processing for synchronized robotics capture streams

Data types

ImageVideoSensorTime seriesGeospatial2D and 3D pose, depth, point clouds, camera trajectories, object geometry, and mesh assets

Industries

TechnologyManufacturingAgricultureTransport and logisticsResearchJewellery, textiles, embodied AI, and simulation workflows

Geographic coverage

IndiaGlobal

Languages

English

Delivery formats

JsonParquetAPI deliveryImagesVideoPLY, OBJ, GLB, depth maps, point clouds, calibration bundles, ROS-compatible outputs, and client schemas

Typical deliverables

Versioned perception outputs with frame and sequence identifiers; calibrated human, hand, camera, and object poses as scoped; dense or sparse depth products; point clouds and reconstructed 3D meshes; confidence and quality metadata; coordinate-system and calibration documentation; processing manifests; exception reports; and optional API or batch-ingestion integration guidance.

Quality assurance

Input validation checks media integrity, calibration, frame ordering, synchronization, and coverage before compute. Output QA includes geometric consistency checks, temporal continuity tests, reprojection and depth sanity checks, confidence thresholds, cross-view agreement where available, sampled expert review, reproducible pipeline versioning, and rerun or exception handling against agreed acceptance criteria.

Compliance and privacy

Buyers define permitted processing, data residency, access, retention, and deletion requirements during scoping. Processing can be separated by project and governed by least-privilege access and controlled transfer procedures. Fenon does not infer permission to process biometric, personal, confidential, or regulated content; those requirements and any required de-identification must be agreed before ingestion.