Apera’s Vue computer recognizes parts from trained CAD models and camera imagery, then estimates poses and plans grasps and collision-avoiding motion. Forge models robot, tooling and work-area geometry before training; reach and gripper choices constrain pickability. VuePort provides model-dependent stereo-camera mounting and Ethernet/PoE interfaces. The manufacturer’s as-low-as-0.3-second figure concerns vision recognition/path planning, and its greater-than-99.99% result concerns simulation training. VuePod V1 packages the workflow for early-access single-SKU ferrous stamped sheet metal up to 15 inches and 4 kg, using a FANUC M-20iD/12L and magnetic gripper.
Technical detail
Core features
CAD-trained object recognition, pose and grasp/path planning
Forge cell simulation with reach/tooling and obstacle constraints
Eye-in-hand XS and fixed eye-to-hand camera options
Vue9.52 joint/linear waypoints and tooling/mechanical diagnostics
VuePod V1 single-SKU ferrous parts, ≤15in/≤4kg, named FANUC robot and magnetic tooling
Apera Vue
Forge simulation
VuePort stereo
CAD training
Pose estimation
VuePod V1
Use & integration
Recorded applications
Industrial bin picking and part handling
Cell modelling and pickability evaluation
Machine tending within the VuePod V1 configuration
These describe the reviewed application scope, not confirmed deployments, released requirements or procurement eligibility.
Evidence of maturity
Manufacturer-marketed industrial platform with a documented UR integration workflow and vendor-derived Hastech/Linamar case coverage. Numerical simulation/vision-cycle claims are not complete-cell acceptance. VuePod V1 is early access; accepted installed performance remains configuration-specific.
Commercial availability
Vue/Forge and VuePort are marketed through Apera sales/support. VuePod V1 early-access suitability depends on the named part, robot and tooling envelope; current versions and delivery commitments require confirmation.
Integration and verification
Readiness
A technology readiness level is not established by the reviewed public sources.
4D vision for industrial robotics may help teams working on Sovereign defence capability areas by contributing to autonomous and uncrewed systems, advanced materials and manufacturing, and protection and survivability.
This is a reviewed public-source assessment. It is not procurement eligibility, endorsement, customer interest, or classified demand.
Original sources 10 linked records
These records support this capability and its published Mission area and Defence need connections. A source count is not a count of independent confirmations.
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · defence applications
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · display lead
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · core features
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · summary
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · technicaldomainslugs
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · technicaldomainslugs
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · capability type
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · commercial availability
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · technicaldomainslugs
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · technical tags
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · technical tags
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · core features
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · maturity
The 2024 eGuide places greater-than-99.99% performance in simulation training. Its as-low-as-0.3-second figure covers recognition/path planning, not a full robot movement or production-cycle guarantee.
Supports: Capability · technology readiness level
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · technicaldomainslugs
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · technical tags
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · summary
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · technology readiness level
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · summary
The 2024 eGuide places greater-than-99.99% performance in simulation training. Its as-low-as-0.3-second figure covers recognition/path planning, not a full robot movement or production-cycle guarantee.
Supports: Capability · capability type
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · defence applications
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · technical tags
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · name
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · maturity
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · core features
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · catalogue teaser
Vue runs on a vision computer, using camera imagery and trained CAD part models to recognize parts, estimate pose, select grasp points and plan collision-avoiding motion, orientation and placement with standard or custom end-of-arm tooling.
Supports: Capability · name
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
Supports: Capability · core features
Apera Vue combines object recognition, pose/path/grasp planning and placement using standard 2D cameras and trained AI. Its workflow starts with CAD geometry and synthetic training; the claimed 99.99 percent reliability is attained in simulation. The 0.3-second figure is a best-case vision cycle, not total robot-cycle time. Vendor-published Hastech/Linamar and Flex-N-Gate examples show industrial use, with customer-specific outcomes.
VuePod V1 supports single-SKU ferrous stamped sheet-metal parts no longer than 15 inches and no heavier than four kilograms, placed from bins into a fixture or jig.
Supports: Capability · defence applications
VuePod V1 supports single-SKU ferrous stamped sheet-metal parts no longer than 15 inches and no heavier than four kilograms, placed from bins into a fixture or jig.
Supports: Capability · display lead
VuePod is in early access with first cells being deployed. Dual-SKU, finished-goods and repack configurations are roadmap items rather than the V1 offering.
Vue 9.52 supports joint/linear movements and approach/retreat waypoints, TCP/tooling visualization, hand-eye mechanical-error diagnostics and VuePort XS range finding for de-racking. January 2026 training estimates are six–24 hours; reliability remains synthetic-cycle manufacturer evidence.
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · display lead
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Supports: Capability · defence applications
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Public sources cited · Facts and assessments kept separate · Human review
VuePod is in early access with first cells being deployed. Dual-SKU, finished-goods and repack configurations are roadmap items rather than the V1 offering.
Supports: Capability · maturity
VuePod is in early access with first cells being deployed. Dual-SKU, finished-goods and repack configurations are roadmap items rather than the V1 offering.
Supports: Capability · commercial availability
VuePod is in early access with first cells being deployed. Dual-SKU, finished-goods and repack configurations are roadmap items rather than the V1 offering.
Supports: Capability · summary
VuePod specifies a FANUC M-20iD/12L, magnetic gripper, rotary regrip, dual VuePort pose checks and wall-mounted HMI; its two-bin layout serves one now/next SKU.
Supports: Capability · technical tags
VuePod V1 supports single-SKU ferrous stamped sheet-metal parts no longer than 15 inches and no heavier than four kilograms, placed from bins into a fixture or jig.
Supports: Capability · summary
VuePod is in early access with first cells being deployed. Dual-SKU, finished-goods and repack configurations are roadmap items rather than the V1 offering.
Supports: Capability · technicaldomainslugs
VuePod specifies a FANUC M-20iD/12L, magnetic gripper, rotary regrip, dual VuePort pose checks and wall-mounted HMI; its two-bin layout serves one now/next SKU.
Supports: Capability · commercial availability
VuePod V1 supports single-SKU ferrous stamped sheet-metal parts no longer than 15 inches and no heavier than four kilograms, placed from bins into a fixture or jig.
Supports: Capability · core features
VuePod specifies a FANUC M-20iD/12L, magnetic gripper, rotary regrip, dual VuePort pose checks and wall-mounted HMI; its two-bin layout serves one now/next SKU.
Supports: Capability · core features
VuePod V1 supports single-SKU ferrous stamped sheet-metal parts no longer than 15 inches and no heavier than four kilograms, placed from bins into a fixture or jig.
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · core features
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · technicaldomainslugs
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · core features
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · commercial availability
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · summary
VuePort has two 12 MP 4000×3000 CMOS cameras, Gigabit Ethernet/M12 X-coded PoE interfaces and processing in the vision controller. XS is eye-in-hand; S/M/M+/L/LT are fixed eye-to-hand options. IP65/IP67 are supplier ratings dependent on model.
Supports: Capability · technical tags
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Supports: Capability · defence applications
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Supports: Capability · catalogue teaser
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Supports: Capability · technicaldomainslugs
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Supports: Capability · core features
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
Supports: Capability · display lead
Browser-based Forge models robot, parts, tooling, cameras, bins and obstacles, evaluates pickability, and sends trained assets to Vue. Robot reach, gripper angle and pick-point diversity constrain emptying; its worked example needs gripper redesign or bin repositioning.
The official capability material supports the named 4D vision for industrial robotics offering and the bounded operational description prepared for reviewer consideration.
Supports: Defence need · Sovereign defence capability areas
The official capability material supports the named 4D vision for industrial robotics offering and the bounded operational description prepared for reviewer consideration.
The 2022 UR guide assumes URCap3.4 and Vue≥8, calibrated cameras, Vue server IP and vision-pipeline ID. Robot calibration follows camera recalibration/movement; robot code waits for image capture before obscuring the bin and handles no-pose outcomes. Current version compatibility is not established by this guide.
A3’s June 24, 2025 editorial describes three Hastech/Linamar ABB/Vue cells and custom tooling for transmission disks, but its linked case video is explicitly Apera-authored. This is vendor-derived case coverage, not direct independently measured buyer acceptance.
Apera lists Ste501,134 Abbott St,Vancouver BC V6B2K4 and Canadian phone +1 6042004544 with sales/support routing. It separately lists its US centre at 23399 Commerce Drive,SuiteB2,Farmington Hills MI48335.
Supports: Defence need · Sovereign defence capability areas
Canada needs secure strategic autonomy and reliable access to capabilities that are critical to defending its sovereignty and meeting allied commitments, while reducing exposure to foreign supply-chain and intellectual-property dependencies.
Supports: Defence need · Sovereign defence capability areas
Reviewer synthesis of the public end state: Canada can build, sustain or control priority aerospace, ammunition, digital, in-service support, sensor, space, specialized manufacturing, training and uncrewed capabilities through domestic strength, trusted partnerships and sovereign access.
