Surgical Robot Haptic Feedback Patents 2026 — PatSnap Eureka
Surgical Robot Teleoperation Haptic Feedback Patents
Haptic feedback in surgical teleoperation spans force sensing, model-augmented rendering, vision-derived synthesis, and navigation-linked virtual fixtures. This dataset covers 60+ patent and literature records from 2006 to 2026 across US, WO, EP, IN, AU, CA, and SG jurisdictions.
Four Mechanism Families Define the Haptic Feedback Landscape
Haptic feedback in surgical teleoperation refers to the closed-loop return of force, torque, tactile, vibrational, and thermal signals from a remote robotic instrument to the surgeon’s hand interface. The core challenge is the transparency-stability trade-off: full fidelity force transmission across a time-delayed network introduces oscillatory instability, while aggressive stability filtering strips out clinically useful tissue-interaction information.
The field divides into four principal mechanism families: direct force sensing and bilateral control using strain gauge or torque sensor arrays; model-augmented predictive haptic rendering using Kelvin–Voigt and Hunt–Crossley tissue models; vision/image-derived haptic synthesis using machine learning on endoscopic video; and navigation-linked adaptive haptic cueing using pre-operative plan-derived virtual boundaries.
Literature evidence quantifies the safety benefit: without haptic feedback, median maximum applied intracorporeal forces reach 6.43 N versus 3.57 N with feedback in standardized robotic circle-drawing tasks. Force feedback reduces tissue loading directly, making it clinically relevant across minimally invasive, orthopedic, neurosurgical, endovascular, and telemedicine domains.
In this dataset, US is the dominant filing jurisdiction, with WO (PCT) second, and India emerging as a notable secondary jurisdiction in 2025–2026 filings. Innovation in retrieved records is concentrated among a small number of large US-based medical robotics companies alongside one active IP-holding entity and several university assignees.
Filing Activity by Technology Cluster and Jurisdiction
The dataset’s densest filing cluster falls in 2021–2026, driven by AI-integration, navigation-linked haptic adjustment, and multi-modal telesurgery architectures. US remains the dominant jurisdiction, with India emerging in 2025–2026.
Patent Filings by Technology Cluster (In This Dataset)
In this dataset, navigation-linked adaptive haptic systems and ML-visual-haptic synthesis account for the highest combined filing activity among the four principal mechanism clusters, with direct force sensing establishing the foundational base from 2006 onward.
↗ Click bars to exploreFiling Activity by Period (In This Dataset)
In this dataset, the 2021–2026 period shows the highest filing concentration, reflecting convergence of AI integration, 5G telesurgery, and navigation-linked haptic adjustment as dominant innovation themes.
↗ Click bars to exploreKey Application Domains for Surgical Haptic Feedback
Within this dataset, haptic feedback patents and literature span six distinct surgical and training domains, from minimally invasive laparoscopic procedures to rural telemedicine and immersive simulation platforms.
Minimally Invasive Laparoscopic Surgery
The largest application domain in this dataset. Literature quantifies that without haptic feedback, median maximum applied intracorporeal forces reach 6.43 N versus 3.57 N with feedback in standardized robotic circle-drawing tasks. Intuitive Surgical Operations’ variable force scaling telerobotic system (US 2018, US 2020) and Cilag GmbH International’s handheld haptic device portfolios (US 2016, 2017, 2025) are the primary patent holders in this domain.
Force FeedbackOrthopedic and Spine Surgery
Mako Surgical Corp. (Stryker) holds a focused portfolio in this domain spanning US, WO, AU, and EP jurisdictions (2021–2026). The robotic spine surgery haptic interface emulates real-time screw-bone interaction forces at a rotational actuator and prevents undesired rotation under unsafe conditions. Pedicle screw placement and knee/cranial bone milling are validated test scenarios for haptic guidance augmentation per literature in this dataset.
Navigation-Linked HapticsTelemedicine and Rural Telesurgery
Multi-modal feedback systems targeting communication-delayed environments appear in Indian filings from Meenakshi Academy of Higher Education and Research (IN 2025) and Preethika Immaculate Britto (IN 2013). The 2025 filing incorporates 5G/satellite/fiber redundant channels, AI latency prediction, blockchain audit, and thermal haptic modalities. Softacuity’s robotic telesurgery portal (WO 2024) also addresses networked telesurgery with multi-channel communication architectures.
Networked TelesurgerySurgical Training and Simulation
KindHeart’s telerobotic training system (WO 2016, EP 2018×2) enables remote proctoring over animal tissue with haptic feedback. Marion Surgical’s VR surgical system with haptic feedback targets simulation of multiple instruments and procedures (WO 2019, US 2019, US 2023). Handshake VR and Anvari (CA/US/WO 2007–2009) defined haptic-enabled laparoscopic-to-telerobotic training transitions, establishing the foundational IP lineage for this sub-domain.
Haptic TrainingKey Patent Assignees in Surgical Haptic Teleoperation — Dataset Snapshot
In this dataset, three assignees — Auris Health, IX Innovation LLC, and Mako Surgical Corp. — each account for 5 retrieved patent records, representing the highest filing concentration in retrieved records among the 10 named assignees with two or more filings.
Top Assignees by Filing Count in Retrieved Records (Dataset Snapshot)
↗ Click bars to exploreAuris Health, Inc.
Auris Health holds 5 patent records in this dataset spanning 2019–2026, making it the highest-volume assignee in retrieved records. Its core portfolio centers on machine-learning-based visual-haptic feedback systems (US 2019, US 2020, US 2021, US 2024×2) that infer tissue interaction forces from endoscopic video frames, with a 2019–2024 priority continuation chain. The most recent filing (WO 2026, pending) introduces a haptic system deriving collision and joint-limit feedback from discrepancy between commanded and resulting robotic arm poses, eliminating dedicated tip force sensing for safety-critical modalities.
United StatesIX Innovation LLC
IX Innovation LLC holds 5 US patent records in this dataset covering 2023–2025, forming a continuous family focused on real-time adjustment of haptic feedback in surgical robots. Each filing uses a navigational confidence score — derived from comparison of pre-operative and intra-operative images — to drive the timing, location, type, and amplitude of haptic response at the surgeon interface. The active US family (2023, 2023, 2024, 2025, 2025) represents a tightly clustered IP position that any new entrant in navigation-linked haptic adjustment must conduct freedom-to-operate analysis against.
United StatesFive Emerging Directions in Surgical Haptic Teleoperation (2025–2026)
The 2021–2026 filing cluster introduces five distinct innovation vectors that extend beyond traditional bilateral force control: AI-generated simulation for decision support, arm-pose-derived safety feedback, multi-modal 5G/blockchain telesurgery, miniaturized multi-sensor robotic heads, and wearable upper-body haptic garments.
AI-Generated Simulation and Visual-Haptic Decision Support
Verb Surgical’s WO 2025 filing introduces a surgical simulation model that generates video representations of simulated task performance in response to user manipulation of input devices. This marks a shift from pure force rendering toward predictive, AI-mediated haptic-visual coupling where the surgeon interacts with a simulated environment rather than awaiting real-time sensor data. The architecture combines teleoperation input handling with AI inference to produce both visual and haptic decision-support outputs simultaneously.
Robotic Arm Pose-Derived Collision and Limit Haptic Feedback
Auris Health’s WO 2026 pending filing derives collision and joint-limit awareness from the discrepancy between commanded and resulting robotic arm poses, feeding this state back through the human input device. This architecture eliminates dedicated force sensing at the tool tip for safety-critical feedback modalities, offering a sensor-reduced pathway to arm safety awareness. The approach is distinct from end-effector tissue force sensing and targets robot kinematic boundary conditions rather than tissue interaction.
Direct Force Sensing vs. ML-Visual-Haptic Synthesis: Mechanism Comparison
Click any row to explore further.
| Dimension | Direct Force Sensing & Bilateral Control | ML-Visual-Haptic Synthesis |
|---|---|---|
| Core mechanism | Strain gauge or torque sensor arrays on end-effector relay measured interaction forces to actuated master controller | Machine learning model infers tissue interaction force from endoscopic video frames; predicted force delivered as haptic signal |
| Latency sensitivity | High — round-trip network delay directly degrades fidelity and risks oscillatory instability | Lower — inference runs locally on video stream; not dependent on round-trip force sensor data transmission |
| Sensor hardware required | Dedicated force/torque sensors mounted on robotic end-effector; adds mechanical complexity and sterilization burden | No dedicated force sensor at tool tip required; relies on existing endoscopic camera feed |
| Key assignees in dataset | Cilag GmbH International (US 2016, 2017, 2025); The Johns Hopkins University (WO 2012, US 2014); Intuitive Surgical Operations (US 2018, US 2020) | Auris Health, Inc. (US 2019–2024, WO 2026); Verb Surgical Inc. (WO 2020, EP 2025, WO 2025) |
| Transparency-stability trade-off | Full fidelity force transmission across time-delayed network risks oscillatory instability; stability filters reduce clinical information | Local inference bypasses round-trip latency; stability is improved but force prediction accuracy depends on ML model quality |
| Validated use cases | Laparoscopic circle-drawing tasks (6.43 N vs. 3.57 N median force reduction); vitreoretinal micro-force sensing; robotic suturing | Surgical task type classification; tool-tissue interaction force level prediction; sensor-inaccessible platforms (flexible endoscopes, catheter robots) |
| Regulatory status | Foundational technology; established in commercial platforms (Intuitive Surgical, Cilag/Ethicon) | Active continuation IP chain (Auris Health 2019–2024); no confirmed commercial regulatory clearance noted in dataset |
Frequently Asked Questions: Surgical Robot Haptic Feedback Patents
According to this dataset, the four principal mechanism families are: (1) direct force sensing and bilateral master-slave control using strain gauge or torque sensor arrays; (2) model-augmented and predictive haptic rendering using Kelvin–Voigt or Hunt–Crossley tissue models estimated at the slave side; (3) vision/image-derived haptic synthesis using machine learning on endoscopic video to infer contact force; and (4) navigation-linked adaptive and virtual-fixture haptic systems coupling pre-operative imaging plans to real-time feedback amplitude.
In this dataset, Auris Health, Inc., IX Innovation LLC, and Mako Surgical Corp. each hold 5 patent records — the highest count among retrieved records. KindHeart, Inc. holds 4 records. Cilag GmbH International, Intuitive Surgical Operations, and Verb Surgical Inc. each hold 3 records. These counts reflect retrieved records only and do not represent total industry output.
The transparency-stability trade-off refers to the tension between full fidelity force transmission and system stability across a time-delayed network. Full fidelity transmission across a network delay introduces oscillatory instability, while aggressive stability filtering strips out clinically useful tissue-interaction information. Model-augmented rendering and ML-visual-haptic synthesis are the two approaches in this dataset that attempt to bypass this trade-off by eliminating dependence on round-trip sensor data.
IX Innovation LLC’s 5 US patent records (2023–2025) describe a system where a navigational confidence score — derived from comparison of pre-operative and intra-operative images — drives the timing, location, type, and amplitude of haptic response delivered to the surgeon interface. The family covers real-time adjustment of haptic feedback in surgical robots and represents a tightly clustered US IP position in navigation-linked haptic adjustment.
Literature within this dataset documents that without haptic feedback, median maximum applied intracorporeal forces reach 6.43 N, compared to 3.57 N with haptic feedback, in standardized robotic circle-drawing tasks using a novel surgical robotic system. This represents a direct reduction in tissue loading attributed to the presence of force feedback.
The 2025–2026 filings include: Meenakshi Academy’s IN 2025 system combining 5G/satellite/fiber redundant channels, AI latency prediction, blockchain audit, and thermal haptic modalities; Softacuity’s WO 2024 telesurgery portal addressing networked multi-channel communication; Hito Robotics’ IN 2026 miniaturized tendon-driven system integrating force, torque, IMU, proximity, pressure, temperature, and biochemical sensors; and Verb Surgical’s WO 2025 AI-generated simulation and decision-support teleoperation system.
Data and insights on this page are based on a limited patent and literature dataset and are for reference only. Figures may not represent the complete technology landscape.