DeepAI AI Chat
Log In Sign Up

Visibility-Inspired Models of Touch Sensors for Navigation

03/04/2022
by   Kshitij Tiwari, et al.
University of Oulu
1

This paper introduces mathematical models of touch sensors for mobile robotics based on visibility. Serving a purpose similar to the pinhole camera model for computer vision, the introduced models are expected to provide a useful, idealized characterization of task-relevant information that can be inferred from their outputs or observations. This allows direct comparisons to be made between traditional depth sensors, highlighting cases in which touch sensing may be interchangeable with time of flight or vision sensors, and characterizing unique advantages provided by touch sensing. The models include contact detection, compression, load bearing, and deflection. The results could serve as a basic building block for innovative touch sensor designs for mobile robot sensor fusion systems.

READ FULL TEXT

page 1

page 2

page 3

page 4

06/07/2022

Sensors for Mobile Robots

A sensor is a device that converts a physical parameter or an environmen...
10/22/2022

Whisker-Inspired Tactile Sensing for Contact Localization on Robot Manipulators

Perceiving the environment through touch is important for robots to reac...
06/07/2020

Every Action Based Sensor

In studying robots and planning problems, a basic question is what is th...
08/31/2021

Through the Looking Glass: Diminishing Occlusions in Robot Vision Systems with Mirror Reflections

The quality of robot vision greatly affects the performance of automatio...
10/09/2019

Mobile Sensor Networks: Bounds on Capacity and Complexity of Realizability

We study the models, proposed by Chen Gu et al. in 2018, of mobile senso...
03/17/2022

A Learning Framework for Bandwidth-Efficient Distributed Inference in Wireless IoT

In wireless Internet of things (IoT), the sensors usually have limited b...
06/01/2021

Lattices of sensors reconsidered when less information is preferred

To treat sensing limitations (with uncertainty in both conflation of inf...