266 citations · 431 across the 7 of their papers we have counts for
6 papers · 1 filter
A Heteroscedastic Likelihood Model for Two-frame Optical Flow
Timothy Farnworth, Christopher Renton, Reuben Strydom +2
Machine vision is an important sensing technology used in mobile robotic systems. Advancing the autonomy of such systems requires accurate characterisation of sensor uncertainty. V…
A Sweet Pepper Harvesting Robot for Protected Cropping Environments
Chris Lehnert, Chris McCool, Inkyu Sa +1
Using robots to harvest sweet peppers in protected cropping environments has remained unsolved despite considerable effort by the research community over several decades. In this p…
In-Field Peduncle Detection of Sweet Peppers for Robotic Harvesting: a comparative study
Chris Lehnert, Chris McCool, Tristan Perez
Robotic harvesting of crops has the potential to disrupt current agricultural practices. A key element to enabling robotic harvesting is to safely remove the crop from the plant wh…
Lessons Learnt from Field Trials of a Robotic Sweet Pepper Harvester
Christopher Lehnert, Christopher McCool, Tristan Perez
In this paper, we present the lessons learnt during the development of a new robotic harvester (Harvey) that can autonomously harvest sweet pepper (capsicum) in protected cropping…
Autonomous Sweet Pepper Harvesting for Protected Cropping Systems
Chris Lehnert, Andrew English, Chris McCool +2
In this letter, we present a new robotic harvester (Harvey) that can autonomously harvest sweet pepper in protected cropping environments. Our approach combines effective vision al…
Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting - Combined Colour and 3D Information
Inkyu Sa, Chris Lehnert, Andrew English +4
This paper presents a 3D visual detection method for the challenging task of detecting peduncles of sweet peppers (Capsicum annuum) in the field. Cutting the peduncle cleanly is on…