For an intelligent agricultural robot to reliably operate on a large-scale farm, it is crucial to accurately estimate its pose. In large outdoor environments, 3D LiDAR is a preferred sensor. Urban and agricultural scenarios are characteristically different, where the latter contains many poorly defined objects such as grass and trees with leaves that will generate noisy sensor signals. While state-of-the-art methods of state estimation using LiDAR, such as LiDAR odometry and mapping (LOAM), work well in urban scenarios, they will fail in the agricultural domain.

3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. This paper presents a deep learning method, Deep-3DMTS for creating a single-perspective approach for 3DMTS through the use of a Convolutional Neural Network (CNN). The novel method is developed and validated via simulation against the standard 3DMTS approach.

This paper proposes a bionic electric spraying rod to perform the crop watering and spraying in the farm. The design concept of multiple vertebrae structures of snake is used to realize a reproducible snake bone arm and muscles of snake, which can be regarded as multiple sets of thin wires and be pulled and released through driver module. It results in different attitudes of the snake bone arm. A water pipe is installed in the snake arm connected to the spray nozzle for spraying. The mobile application interface (APP) is designed to provide the user to control the arm remotely.

The new Constitution of Nepal (2015) has initiated federal, provincial, and local governments in Nepal, each bestowed with respective rights, responsibilities, power and authority. While developing the new mechanism of governance, the Constitution has given immense authority as well as responsibility to local governments, which is unprecedented and has never been experienced before in the history of Nepal. Along with the restructuring of the state, the institutional mechanism of the agriculture sector has also been restructured.

Mounting evidence points to the fact that climate change is already affecting agriculture and food security, which will therefore make the challenge of ending hunger, achieving food security, improving nutrition, and promoting sustainable agriculture even more difficult (FAO 2016). Through Sustainable Development Goal (SDG) 13, the 2030 Agenda calls for strengthened resilience and adaptive capacity in response to natural hazards and climate-related disasters globally.

The Feed the Future Mozambique Agricultural Innovations Activity (FTF Inova) made good progress on its interventions during quarter (Q) 2 of fiscal year (FY) 2019, facilitating the introduction and adaptation of a number of innovations with an increasing portfolio of partners. Testing of established probes continued, accompanied by the first set of learning, while new probes also emerged.