Obstacle detection, localization, and avoidance for autonomous robotic seeding**
Obstacle detection, localization, and avoidance for autonomous robotic seeding**
批准号:
533707-2018
负责人:
JanabiSharifi, Farrokh
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31
中文摘要
劳动力成本和可用性被认为是加拿大农业面临的最大挑战。作为SeedMaster的一部分,DOT技术公司将创造一个自主动力单元,作为主要的运动系统,用于携带大量用于播种、施肥和耕作的农具。这种简单的自主动力装置将使农民能够通过一个名为DOT的共享、更小、更经济的运动基地来实现许多农场功能。虽然有大量关于轮式机器人/车辆在室内/室外应用中的自主导航的文献,但在农场使用的自主机器领域的研究仍处于起步阶段。****该公司的计划是迎接挑战,提供低成本,但现实世界的机器人解决方案,在农业行业执行任务。该公司计划制造一种自主动力装置,作为主要的运动系统(即DOT),用于携带大量用于播种、施肥、修剪和耕作的农具。该项目的目标是通过开发:(i)使用RGB\D相机来提高农场移动系统(DOT)的可靠性,而不是使用忽略移动障碍物和更重要的人类的预先绘制的地图来使用先进的障碍物检测,定位和回避技术;(ii)精确的作物行检测和跟踪方法,使机器人能够基于图像进行定位和路径规划,从而最大限度地提高操作效率(例如,在田间均匀播种等耕作任务)。****开发和整合所提出的方法将扩大公司的市场和竞争力。除了对公司有利外,拟议的工作还将为从事该项目和/或其延续的研究生和博士后创造培训和工作机会
英文摘要
Labor cost and availability are identified as the biggest challenges facing Canadian agriculture. The DOT Technology Corporation, as a part of the SeedMaster, is to create an autonomous power unit that acts as a primary locomotion system for carrying a multitude of farm implements used for seeding, fertilizing, and tilling. This simple autonomous power unit will enable farmers to employ a number of farm functions through a shared, smaller, and economical locomotion base, called DOT. While there is a huge body of literature on autonomous navigation of wheeled robots/vehicles in indoor/outdoor applications, the research in the realm of autonomous machines used in farms remains at its infancy. ****The plan of the company is to meet the challenges of delivering low cost, yet real-world robotic solutions for performing tasks in the agriculture industry. The company plans to create an autonomous power unit that acts as a primary locomotion system (namely DOT) for carrying a multitude of farm implements used for seeding, fertilizing, pruning and tilling. The objectives of this project are to enhance reliability of farm mobility system (DOT) by developing: (i) advanced obstacle detection, localization, and avoidance techniques using an RGB\D camera, instead of pre-sketched maps ignoring mobile obstacles and more importantly human beings; and (ii) accurate crop-row detection and tracking method to enable image-based localization and path planning of the robot to maximize operation efficiency (e.g., conducting farming tasks such as seeding evenly across the field). ****Development and integration of the proposed methods will expand the company's market and competitiveness. In addition to the benefits to the company, the proposed work will create training and job opportunities for the graduate students and postdoctoral fellows engaged in this project and/or its continuation.**
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