Manipulating and Perceiving Simultaneously (MAPS) for Haptic Object Recognition

这个SGER项目是一个可行性研究算法的操纵和识别使用触觉信息。MAPS（Manipulation-and-Perceiving-Simultaneously）范式借鉴了同时定位和映射（SLAM）和视觉对象识别的最新进展，并进行了必要的修改以使其适应触觉探索。在MAPS中，探索是由定位承载关于对象的高信息含量的“感兴趣区域”的目标驱动的。这些兴趣点的触觉特性将与位置信息一起以独立于坐标系的方式进行编码。在学习阶段，将获取大量这样的点并存储在数据库中。在识别过程中，新获取的点将与数据库中的点进行比较，以生成合理的模型假设。最后的识别决定也将包括隐含在表面结构的位置和方向中的几何约束。该项目的主要贡献将是：-发展主动探索战略，以提取、定位和绘制独特的表面特征;-发展和评估以触觉为基础的物体识别算法，利用空间和触觉“外观”信息;- 开发一个实验环境，以执行和评估MAPS算法。

This SGER project is a feasibility study of algorithms for manipulation and recognition using haptic information. The Manipulation-and-Perceiving-Simultaneously (MAPS) paradigm borrows key ideas from recent advances in simultaneous localization and mapping (SLAM) and visual object recognition with modifications necessary to adapt them to haptic exploration.In MAPS, exploration is driven by the objective of locating "interest areas" that carry high information content about the object. The haptic properties of these interest points will be encoded, together with location information, in a coordinate-system independent fashion. During a learning phase, a large set of such points will be acquired and stored in a database. During recognition, newly acquired points will be compared with those in the database to generate plausible model hypotheses. The final recognition decision will also incorporate the geometric constraints implicit in the location and orientation of the surface structure.The key contributions of this project will be:- The development of active exploration strategies to extract, localize and map distinctive surface features;- The development and evaluation of haptics-based object recognition algorithms using both spatial and haptic "appearance" information; - The development of an experimental environment to implement and evaluate MAPS algorithms.