266 citations · 470 across the 18 of their papers we have counts for
8 papers · 1 filter
Design of a Multi-Modal End-Effector and Grasping System: How Integrated Design helped win the Amazon Robotics Challenge
S. Wade-McCue, N. Kelly-Boxall, M. McTaggart +19
We present the grasping system and design approach behind Cartman, the winning entrant in the 2017 Amazon Robotics Challenge. We investigate the design processes leading up to the…
Mechanical Design of a Cartesian Manipulator for Warehouse Pick and Place
M. McTaggart, D. Morrison, A. W. Tow +8
Robotic manipulation and grasping in cluttered and unstructured environments is a current challenge for robotics. Enabling robots to operate in these challenging environments have…
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…
Semantic Segmentation from Limited Training Data
A. Milan, T. Pham, K. Vijay +22
We present our approach for robotic perception in cluttered scenes that led to winning the recent Amazon Robotics Challenge (ARC) 2017. Next to small objects with shiny and transpa…
Cartman: The low-cost Cartesian Manipulator that won the Amazon Robotics Challenge
D. Morrison, A. W. Tow, M. McTaggart +19
The Amazon Robotics Challenge enlisted sixteen teams to each design a pick-and-place robot for autonomous warehousing, addressing development in robotic vision and manipulation. Th…
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…