Geometric Calibration of a Time-of-Flight Depth Sensor and a Colour Camera Pair

Author(s):  
Kartik E. Cholachgudda ◽  
Rajashekhar C. Biradar ◽  
M. Lokanath
Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1156
Author(s):  
Eu-Tteum Baek ◽  
Hyung-Jeong Yang ◽  
Soo-Hyung Kim ◽  
Gueesang Lee ◽  
Hieyong Jeong

A distance map captured using a time-of-flight (ToF) depth sensor has fundamental problems, such as ambiguous depth information in shiny or dark surfaces, optical noise, and mismatched boundaries. Severe depth errors exist in shiny and dark surfaces owing to excess reflection and excess absorption of light, respectively. Dealing with this problem has been a challenge due to the inherent hardware limitations of ToF, which measures the distance using the number of reflected photons. This study proposes a distance error correction method using three ToF sensors, set to different integration times to address the ambiguity in depth information. First, the three ToF depth sensors are installed horizontally at different integration times to capture distance maps at different integration times. Given the amplitude maps and error regions are estimated based on the amount of light, the estimated error regions are refined by exploiting the accurate depth information from the neighboring depth sensors that use different integration times. Moreover, we propose a new optical noise reduction filter that considers the distribution of the depth information biased toward one side. Experimental results verified that the proposed method overcomes the drawbacks of ToF cameras and provides enhanced distance maps.


2013 ◽  
Vol 48 (2) ◽  
pp. 559-572 ◽  
Author(s):  
Cristiano Niclass ◽  
Mineki Soga ◽  
Hiroyuki Matsubara ◽  
Satoru Kato ◽  
Manabu Kagami
Keyword(s):  

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775369 ◽  
Author(s):  
Dong-Hyun Lee ◽  
Brian Coltin ◽  
Theodore Morse ◽  
In-Won Park ◽  
Lorenzo Flückiger ◽  
...  

We present a handrail detection and pose estimation algorithm for the free-flying Astrobee robots that will operate inside the International Space Station. The Astrobee will be equipped with a single time-of-flight depth sensor and a compliant perching arm to grab the International Space Station handrails. Autonomous perching enables a free-flying robot to minimize power consumption by holding its position without using propulsion. Astrobee is a small robot with many competing demands on its computing, power, and volume resources. Therefore, for perching, we were limited to using a single compact sensor and a lightweight detection algorithm. Moreover, the handrails on the International Space Station are surrounded by various instruments and cables, and the lighting conditions change significantly depending on the light sources, time, and robot location. The proposed algorithm uses a time-of-flight depth sensor for handrail perception under varying lighting conditions and utilizes the geometric characteristics of the handrails for robust detection and pose estimation. We demonstrate the robustness and accuracy of the algorithm in various environment scenarios.


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