Design and optimization of a modular autonomous micro-robotic gripper for delicate object manipulation

Project Abstract

This research presents the design, optimization, and validation of a modular autonomous micro-robotic gripper tailored for delicate object manipulation across biomedical, electronics, and food-packaging domains. The gripper integrates soft robotics, modular actuation, and real-time perception to achieve high-fidelity grip, adaptable contact mechanics, and autonomous decision-making in unstructured environments. A multi-layered approach combines a compliant, elastomeric finger array with embedded microactuators and flexible sensorized skins to realize safe interaction with fragile items such as fruits, delicate biological samples, and thin-wilm materials, while maintaining piconewton-to-micronewton force resolution where required. The modular architecture enables rapid reconfiguration for variable object geometries, grasp types (enveloping, precision, and pinch), and task-specific end-effectors, reducing tooling downtime and enabling on-demand customization in compact lab-on-a-chip or micro-assembly settings. A core contribution lies in the integration of tendonless, electroactive polymer actuators with compliant, bio-inspired finger kinematics that yield highly directional stiffness modulation and controllable grip force gradients. This is complemented by a compact proprioceptive-and-exteroceptive sensing suite, including capacitive tactile skins, optical proximity sensors, and embedded micro force sensors, to provide robust state estimation under occlusion and vibration. The software stack features a hierarchical control framework combining model-based planning with data-driven torque and contact force estimation, enabling real-time adaption to object compliance, deformation, and surface friction. A vision-enabled perception layer leveraging low-power photometric and depth sensing guides grasp planning and pose estimation, while a learning-based gripper policy optimizes grip selection and force allocation for novel objects encountered during autonomous operation. The optimization workflow formalizes a multi-objective problem balancing grasp stability, contact safety, energy efficiency, and hardware modularity. It employs surrogate modeling, topology optimization for internal channels in the gripper body, and genetic algorithms to explore actuator and sensor placements that minimize actuation energy while maximizing adaptability and reliability. Finite element analysis informs material selection and stress distribution under repeated contact, ensuring durability for long-term deployment. Validation experiments encompass a spectrum of delicate objects with varying stiffness, texture, and geometry, including fresh produce, gelatinous samples, and thin-film substrates. Performance metrics focus on grip force controllability, slip resistance under perturbation, grasp success rate, object deformation, cycle life, and response latency. The results demonstrate that the modular gripper achieves stable, adaptive grasps with minimal object damage, while maintaining rapid reconfiguration between grasp modalities within seconds. Comparative studies against rigid and non-modular counterparts reveal superior adaptability and reduced risk of object fracture. The work advances the state of the art in micro-robotic manipulation by delivering a scalable, autonomous, and soft-contact gripper solution with validated design guidelines, control architectures, and optimization strategies. Potential applications span automated handling in micro-assembly lines, minimally invasive surgical tooling support, and high-value fragile material handling, with a path toward field-ready deployment in compact, energy-constrained platforms.

Project Overview

What This Project Is About

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A straightforward, hands-on project about designing a small, modular gripper that can be controlled by a computer to pick up and release very delicate objects. The aim is to create a gripper that can adjust its grip and shape to handle different items without damaging them.

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The Problem It Addresses

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Many robotic grippers either lack flexibility or are too fragile for delicate items. This project seeks a versatile, adjustable gripper system that can handle fragile objects (like fruits, small components, or soft materials) while being reliable and easy to assemble.

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Objectives of the Project

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1. Design a modular gripper with swappable fingers.
2. Incorporate a simple actuation method that can be controlled precisely.
3. Develop a control strategy to adjust grip strength and finger positions automatically.
4. Test grip on several delicate items and measure success rates.
5. Evaluate durability and ease of assembly for end users.

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What You Will Do Step by Step

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1) Research existing grippers and choose a modular approach. 2) Create design sketches and select materials. 3) Build a small prototype with basic sensors. 4) Implement a control program to open/close grip and adjust force. 5) Test with different objects and record results. 6) Analyze data to find what works best. 7) Refine the design for reliability. 8) Document the process and prepare a final report.

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Expected Outcome

Expect a working modular micro-gripper that can pick up delicate items without damage, with clear guidelines for assembly and operation. The project should deliver a practical prototype, testing data, and design recommendations for future improvements.