A Biomimetic Approach based on Tactile Sensing for Stable Grasp and Manipulation using Biomechatronic Hand Prostheses and Assistive Robots

基于触觉传感的仿生方法，使用生物机电假手和辅助机器人实现稳定抓取和操作

• 批准号: RGPIN-2022-05226
• 负责人: Mohebbi, Abolfazl
• 金额: $ 1.82万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754479
• 关键词: Biomimetic; Approach; based; Tactile; Sensing

Tactile sensing is a fundamental component of how humans interact with their environment. With the loss of a limb in the upper body, the amputees also lose their ability to explore, understand and interact with the surrounding world using their sense of touch. The active hand prostheses used by a variety of amputees are only able to provide crude control over object handling; The users cannot adjust their hand movement for grasping an object or handling a tool without closely looking at it. To increase the acceptance of artificial limbs by amputees, the users should be able to perform enhanced, intuitive motor control and simultaneously feel with their prosthetic limbs. When operating in an unknown environment, tactile sensitivity, in conjunction with other sensory sources, becomes vital for a safe and effective physical interaction and performing complex tasks. In the long-term, I aim to develop a cost-efficient biomechatronic prosthetic hand capable of stable object grasping and in-hand manipulation by incorporating tactile sensing and haptic feedback. This prosthesis will ideally help users through facilitating safe interactions with the environment in various activities of daily living. Inspired by the schemes that humans employ for grasping, handling and moving objects in their hand, this Discovery Grant will be used in a short-term window of 5 years to create a framework for object grasping and manipulation by robotic arms using tactile sensors. I hypothesize that understanding and mimicking the human way of incorporating information from the sense of touch into the process of object handling, will result in devising a more efficient planning and control approach. First, we will develop a machine learning model to learn, from demonstrations, how tactile sensitivity in non-amputee subjects works in collaboration with vision, and how it corresponds to muscle synergies creating motor actions for grasping and manipulating objects. Then, we will formulate an index to assess the stability of a grasp using tactile information without having prior knowledge about the objects and the environment. Using this index, we will subsequently design a reinforcement learning model to fine-tune the control model by learning from successful and failed attempts. Lastly, a haptic interface will be prototyped to control an assistive robotic hand using the developed AI models. At the end, we will validate the effectiveness of the proposed framework by performing grasping and manipulation tasks with both the training set and a set of unknown real-world objects. The haptic interface and control algorithm will directly benefit individuals with neuromuscular disorders and upper-limb amputation in their day-to-day activities, which will hopefully elevate Canada's place as an international leader in the field of assistive and prosthetic robotics.

触觉敏感性是人类与环境互动的基本组成部分。由于上半身失去了肢体，截肢者还失去了探索，理解和与周围世界互动的能力。各种截肢者使用的主动手术只能提供对物体处理的粗略控制；用户无法在不仔细观察的情况下调整手动移动以抓住对象或处理工具。为了增加截肢者对人造四肢的接受，用户应该能够执行增强的，直观的运动控制，并简单地感觉到自己的假肢。当在未知环境中运行时，触觉灵敏度与其他感觉源结合使用，对于安全有效的物理互动和执行复杂的任务至关重要。从长远来看，我旨在开发一种具有成本效益的生物学假肢手，能够通过融合触觉灵敏度和狂热的反馈来稳定对象抓握和手持操作。理想情况下，该假体将通过支持与环境的各种日常生活活动的安全互动来帮助用户。受到人类在手中掌握，处理和移动物体的计划的启发，该发现赠款将在5年的短期窗口中使用，以创建一个使用触觉传感器的机器人臂来抓住对象和操作的框架。我假设理解并模仿人类将信息从接触感中纳入对象处理过程的方式将导致设计更有效的计划和控制方法。首先，我们将开发一个机器学习模型，从演示中学习非开拓者主体中的触觉灵敏度如何与视觉合作工作，以及它与肌肉协同作用为掌握和操纵物体的运动动作而言。然后，我们将制定一个索引来评估使用触觉信息的掌握的稳定性，而无需对物体和环境的事先了解。使用此索引，我们将随后设计一个增强学习模型，以通过成功和失败的尝试来微调控制模型。最后，将使用开发的AI模型进行原型触觉界面来控制辅助机器人手。最后，我们将通过执行训练集和一组未知的现实世界对象来验证所提出的框架的有效性。触觉界面和控制算法将在日常活动中直接使神经肌肉疾病和上限截肢的人受益，这将有望提升加拿大作为辅助和假肢机器人领域的国际领导者的地位。