Human-in-the-Loop Haptic Micromanipulation Platform
Disciplines
- Mechanical Engineering (Mechatronics)
- Computer Science / Robotics
- Biomedical Engineering
Develop an open, modular platform that allows scientists to manipulate microscopic objects using commercial haptic devices while receiving real-time force and virtual haptic feedback.
The project will investigate whether haptic interfaces, computer vision, AI-assisted guidance, and precision micromanipulators can improve the speed, precision, and safety of biological manipulation tasks.
Rather than building a robot that replaces scientists, this project focuses on creating an intelligent instrument that amplifies human skill.
The resulting platform should become the foundation for future BioNanomics research in:
- Single-cell manipulation
- Patch-clamp electrophysiology
- Embryo microinjection
- Organoid manipulation
- Laser capture microdissection
- Optical tweezers
- AI-assisted microscopy
- Tele-operated laboratory robotics
- Design an extensible hardware architecture for haptic micromanipulation.
- Develop an open software platform that integrates commercial laboratory hardware.
- Investigate bilateral haptic feedback at microscopic scales.
- Evaluate synthetic (vision-derived) versus physical force feedback.
- Develop AI-assisted "shared autonomy" that guides rather than replaces the operator.
- Publish all software, interfaces, datasets, and benchmark results.
- Does haptic feedback improve microscopic manipulation accuracy?
- Can computer vision generate useful virtual force fields before physical contact occurs?
- What level of motion scaling produces the best operator performance?
- Can AI reduce accidental collisions while maintaining complete human control?
- Which commercial hardware platforms provide the best foundation for future BioNanomics research?
- Survey bilateral teleoperation
- Survey haptic rendering
- Survey virtual fixtures
- Survey robotic microinjection
- Survey patch-clamp robotics
- Survey force sensing
- Survey optical tweezers
- Survey shared autonomy
- Survey surgical robotics
- Publish a comprehensive literature review suitable for journal submission.
- Okamura, A. M. "Haptic Feedback in Robot-Assisted Surgery."
- Frontiers in Robotics and AI – Haptic Interfaces for Micromanipulation.
- IEEE Transactions on Haptics.
- IEEE International Conference on Robotics and Automation (ICRA).
Build a complete simulation before purchasing laboratory hardware.
System Architecture
Haply Device
↓
Motion Scaling
↓
Virtual Micromanipulator
↓
Virtual Cell
↓
Virtual Force Model
↓
Haptic Feedback
- MuJoCo — https://mujoco.org
- NVIDIA Isaac Sim — https://developer.nvidia.com/isaac-sim
- Drake — https://drake.mit.edu
- Unity — https://unity.com
- Digital twin
- Force model
- Motion scaling model
- Collision detection
- Virtual fixtures
$3,000–5,000
-
Haply Inverse3 Haptic Device
- https://haply.co
- Primary operator interface
-
OpenFlexure Microscope
- https://openflexure.org
- Open-source microscope platform
-
USB3 Machine Vision Camera
- Basler
- FLIR
- Allied Vision
-
3D Printer
- Bambu Lab X1 Carbon
- Prusa MK4S
-
Assorted Linear Rails and Fixtures
- Misumi
- OpenBuilds
- Demonstrate intuitive manipulation of a virtual pipette over microscope imagery.
- Validate operator ergonomics.
- Measure latency.
- Evaluate motion scaling.
$10,000–20,000
-
Zaber Precision Stages
-
Thorlabs Motorized Translation Stages
-
PI (Physik Instrumente) Precision Motion Systems
- Motion scaling
- Tremor suppression
- Clutch operation
- Velocity scaling
- Coordinate transforms
- Workspace calibration
$20,000–60,000
-
Sensapex UMP Micromanipulators
-
Sutter MP-285
-
Scientifica PatchStar
-
Narishige Motorized Manipulators
- API quality
- SDK availability
- Position repeatability
- Latency
- Closed-loop control
- Community adoption
- Maintainability
- Upgrade path
No physical force sensor required.
Investigate synthetic force generation using:
- Image segmentation
- Collision prediction
- Motor current
- Position error
- Velocity
- Acceleration
- Pipette pressure
- AI-based contact estimation
Develop virtual fixtures representing:
- Cell membrane
- Coverslip
- Pipette
- Nucleus
- Organelles
- Forbidden workspaces
$20,000–80,000
-
ATI Industrial Automation Force/Torque Sensors
-
MEMS Force Sensors
-
Strain Gauge Designs
-
Piezoelectric Sensors
-
Capacitive Sensors
-
Vision-Based Force Estimation
- Physical force sensing
- Vision-derived force estimation
- Synthetic force models
Integrate AI as a cooperative assistant.
Evaluate
- Meta Segment Anything (SAM)
- FoundationPose
- NVIDIA Foundation Vision Models
- OpenCV
- ROS2 Perception Stack
Investigate
- Virtual fixtures
- Predictive collision avoidance
- Motion stabilization
- AI-assisted insertion guidance
- Learned manipulation policies
- Design modular mounting hardware.
- Design interchangeable end-effectors.
- Design vibration-isolated microscope interfaces.
- Perform finite element analysis.
- Analyze structural stiffness.
- Analyze resonance frequencies.
- Design calibration fixtures.
- Validate repeatability.
- Develop manufacturable CAD models.
- Develop ROS2 drivers.
- Develop Haply interface.
- Develop manipulator interfaces.
- Develop microscope interfaces.
- Develop calibration software.
- Develop haptic rendering engine.
- Develop data logging.
- Develop replay system.
- Develop benchmarking framework.
- Develop SDK and API.
- Publish open documentation.
Measure
- Position accuracy
- Insertion success rate
- Completion time
- Operator fatigue
- Learning curve
- Collision frequency
- Tissue damage
- Repeatability
- Latency
- User preference
- Expert versus novice performance
| Phase | Estimated Cost |
|---|---|
| Simulation | $2,000 |
| Early Prototype | $5,000 |
| Precision Motion Platform | $15,000 |
| Commercial Micromanipulators | $50,000 |
| Force Sensing | $40,000 |
| AI and Vision Infrastructure | $15,000 |
| Mechanical Fabrication and Tooling | $20,000 |
| Contingency | $25,000 |
| Total Program Estimate | Approximately $170,000 |
The long-term objective is to establish the BioNanomics Haptic Instrumentation Platform (BHIP)—an open, modular ecosystem for precision biological manipulation. BHIP will define standardized interfaces between haptic devices, microscopes, micromanipulators, force sensors, pressure controllers, imaging systems, and AI software. By emphasizing interoperability and reusable software rather than application-specific hardware, the platform will enable future research across patch-clamp electrophysiology, embryo microinjection, organoid surgery, laser capture microdissection, optical tweezers, and AI-assisted laboratory automation, positioning BioNanomics as a leader in next-generation human-in-the-loop scientific instrumentation.