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.

触觉传感是人类与环境交互的基本组成部分。随着上半身肢体的丧失，截肢者也失去了利用触觉探索、理解和与周围世界互动的能力。各种截肢者使用的主动式假肢只能提供粗糙的物体处理控制;使用者在没有仔细观察的情况下无法调整他们的手运动以抓握物体或处理工具。为了增加截肢者对假肢的接受度，使用者应该能够执行增强的、直观的运动控制，同时用他们的假肢感觉。当在未知环境中操作时，触觉灵敏度与其他感官来源相结合，对于安全有效的物理交互和执行复杂任务至关重要。从长远来看，我的目标是开发一个具有成本效益的生物机电假手能够稳定的物体抓取和手操作，结合触觉传感和触觉反馈。这种假肢将理想地帮助用户在日常生活的各种活动中促进与环境的安全互动。受人类用于抓取，处理和移动手中物体的计划的启发，这项发现补助金将在5年的短期窗口内用于创建使用触觉传感器的机器人手臂抓取和操纵物体的框架。我假设，理解和模仿人类的方式，将信息从触觉到对象处理的过程中，将导致设计一个更有效的规划和控制方法。首先，我们将开发一个机器学习模型，从演示中学习非截肢受试者的触觉敏感性如何与视觉合作，以及它如何对应于肌肉协同作用，从而产生抓取和操纵物体的运动动作。然后，我们将制定一个指数，以评估稳定的把握使用触觉信息，而无需事先了解的对象和环境。使用这个指数，我们随后将设计一个强化学习模型，通过从成功和失败的尝试中学习来微调控制模型。最后，触觉接口将被原型化，以使用开发的AI模型控制辅助机器人手。最后，我们将通过使用训练集和一组未知的真实世界物体执行抓取和操作任务来验证所提出的框架的有效性。触觉接口和控制算法将直接使患有神经肌肉疾病和上肢截肢的个体在日常活动中受益，这将有望提升加拿大在辅助和假肢机器人领域的国际领先地位。