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Robotics & Hardware

Marine soft gripper

The Marine soft gripper refers to an open-source soft robotic gripper project known as the Soft Multimodal Gripper (SMG), which is designed for hybrid grasping in cluttered environments. It combines layer jamming and tendon-driven mechanisms to enable adaptable object handling. The system integrates with CoppeliaSim simulation software and uses a deep multistage learning scheme implemented in Python with PyTorch to support grasping in both lightly and highly cluttered scenarios. The project includes datasets for training and requires manual setup of dependencies and simulation scenes. This gripper is targeted at robotics researchers and developers who work on robotic grasping in simulation environments. It provides a full Python codebase that facilitates extension with machine learning libraries and supports multiple physics engines within CoppeliaSim. However, it lacks pre-built releases or packages and depends on specific simulation scenes for operation.

Updated Jan 21, 2026open-source

An open-source soft robotic gripper project combining layer jamming and tendon-driven actuation for hybrid grasping in cluttered simulation environments.

Pricing
0
Category
Robotics & Hardware
Company
Interactive PresentationOpen Fullscreen ↗
01
Combines layer jamming and tendon-driven mechanisms to adaptively grasp objects in cluttered environments.
02
Implements a deep learning scheme using PyTorch to improve grasping performance in simulation.
03
Supports simulation scenes with Vortex physics engine for both lightly and highly cluttered scenarios.
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Written in Python 3 with dependencies including PyTorch, NumPy, OpenCV, SciPy, and Matplotlib for ease of extension.
05
Includes datasets for training grasping models in cluttered environments, requiring manual download and setup.

Robotic Grasping Research

Developing and testing hybrid grasping algorithms in simulated cluttered environments using CoppeliaSim.

Simulation-Based Gripper Development

Experimenting with soft robotic gripper designs that combine layer jamming and tendon actuation for adaptable object handling.

1
Install Dependencies
Install Python 3, PyTorch 1.0 or higher, NumPy, OpenCV-Python, SciPy, Matplotlib, and CoppeliaSim simulation software.
2
Clone Repository and Setup
Clone the GitHub repository and download/unzip the required datasets into the /code directory.
3
Run Simulation
Launch CoppeliaSim, open either simulation-lc.ttt or simulation-hc.ttt scene, and select the Vortex physics engine to start.
4
Contact for Support
Reach out to Fukang Liu at Georgia Tech for questions or further assistance.
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Strategic Context for Marine soft gripper

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Pricing
Model: open-source
Free
0
  • Full access to source code
  • Simulation scenes for cluttered environments
  • Deep learning integration

The project is freely available on GitHub under an open-source license.

Assessment
Strengths
  • Supports grasping in both lightly and highly cluttered simulated environments.
  • Integrates multimodal grasping mechanisms based on prior layer jamming research.
  • Full Python implementation facilitates integration with machine learning tools.
  • Compatible with multiple physics engines in CoppeliaSim.
Limitations
  • Requires manual download and placement of datasets.
  • No pre-built releases or installation packages are provided.
  • Dependent on specific CoppeliaSim simulation scenes for operation.