Sense contact感知接触
Build event-based tactile sensors that capture texture and contact as sparse signals.构建事件驱动触觉传感器，把纹理与接触编码为稀疏信号。
Neuromorphic tactile hardware神经形态触觉硬件Research研究
Teaching robots how to touch with purpose让机器人有目的地触摸世界
I study how robots can actively explore the world through touch. At Bristol Robotics Laboratory, I combine human-inspired movement, neuromorphic tactile sensing and spiking neural networks, then translate those ideas into real-time inspection systems for composite manufacturing.我研究机器人如何像人一样主动通过触觉探索世界。在布里斯托机器人实验室，我将仿生探索动作、神经形态触觉传感与脉冲神经网络结合，并把这些研究转化为面向复合材料制造的实时检测系统。
Explore actively主动探索
Study how speed, motion and contact strategy change what a robot can feel.研究速度、动作与接触策略如何改变机器人的触觉信息。
Human-inspired movement仿人探索动作Compute with spikes脉冲计算
Use spiking neural networks to classify tactile events with low power and latency.使用脉冲神经网络，以低功耗、低延迟方式识别触觉事件。
Efficient neuromorphic models高效神经形态模型Inspect in real time实时检测
Translate laboratory touch into autonomous composite quality assurance.把实验室触觉研究转化为复合材料自主质量检测。
Industrial deployment工业场景落地Current question当前问题
How can a robot choose how to touch, extract useful events, and make a trustworthy decision before energy or time runs out?机器人如何选择触摸方式、提取有效事件，并在能耗或时间耗尽前做出可信决策？
Affiliation所属机构
School of Engineering Mathematics and Technology, University of Bristol
Bristol Robotics Laboratory · Dexterous Group
Supervision导师
- Dr Benjamin Ward-Cherrier
- Dr Martin Pearson
Funding资助
Fully funded by the China Scholarship Council and the University of Bristol由国家留学基金委与布里斯托大学联合全额资助
Collaboration合作交流
Let’s build machines that understand touch.一起让机器真正理解触觉。
I welcome conversations about tactile robotics, neuromorphic sensing, industrial inspection, research communication and relevant career opportunities.欢迎就触觉机器人、神经形态传感、工业检测、科研传播及相关职业机会与我交流。
ao.li@bristol.ac.uk