Raghav Khanna

ETH Zurich | ETH Zürich · Department of Mechanical and Process Engineering

The application of autonomous robots in agriculture is gaining increasing popularity thanks to the high impact it may have on food security, sustainability, resource-use efficiency, reduction of chemical treatments, and optimization of human effort and yield. With this vision, the Flourish research project aimed to develop an adaptable robotic solu...

The ability to plan informative paths online is essential to robot autonomy. In particular, sampling-based approaches are often used as they are capable of using arbitrary information gain formulations. However, they are prone to local minima, resulting in sub-optimal trajectories, and sometimes do not reach global coverage. In this letter, we pres...

Background Recent advances in high throughput phenotyping have made it possible to collect large datasets following plant growth and development over time, and those in machine learning have made inferring phenotypic plant traits from such datasets possible. However, there remains a dirth of datasets following plant growth under stress conditions a...

The application of autonomous robots in agriculture is gaining more and more popularity thanks to the high impact it may have on food security, sustainability, resource use efficiency, reduction of chemical treatments, minimization of the human effort and maximization of yield. The Flourish research project faced this challenge by developing an ada...

The ability to plan informative paths online is essential to robot autonomy. In particular, sampling-based approaches are often used as they are capable of using arbitrary information gain formulations. However, they are prone to local minima, resulting in sub-optimal trajectories, and sometimes do not reach global coverage. In this paper, we prese...

The combination of aerial survey capabilities of Unmanned Aerial Vehicles with targeted intervention abilities of agricultural Unmanned Ground Vehicles can significantly improve the effectiveness of robotic systems applied to precision agriculture. In this context, building and updating a common map of the field is an essential but challenging task...

The combination of aerial survey capabilities of Unmanned Aerial Vehicles with targeted intervention abilities of agricultural Unmanned Ground Vehicles can significantly improve the effectiveness of robotic systems applied to precision agriculture. In this context, building and updating a common map of the field is an essential but challenging task...

The ability to automatically monitor agricultural fields is an important capability in precision farming, enabling steps towards more sustainable agriculture. Precise, high-resolution monitoring is a key prerequisite for targeted intervention and the selective application of agro-chemicals. The main goal of this paper is developing a novel crop/wee...

We present a novel weed segmentation and mapping framework that processes multispectral images obtained from an unmanned aerial vehicle (UAV) using a deep neural network (DNN). Most studies on crop/weed semantic segmentation only consider single images for processing and classification. Images taken by UAVs often cover only a few hundred square met...

The Flourish project aims to bridge the gap between current and desired capabilities of agricultural robots by developing an adaptable robotic solution for precision farming. Combining the aerial survey capabilities of a small autonomous multi-copter Unmanned Aerial Vehicle (UAV) with a multipurpose agricultural Unmanned Ground Vehicle (UGV), the s...

In many unmanned aerial vehicle (UAV) applications, flexible trajectory generation algorithms are required to enable high levels of autonomy for critical mission phases, such as take-off, area coverage, and landing. In this paper, we present a guidance approach which uses the improved intrinsic tau guidance theory to create spatio-temporal 4-D traj...

Autonomous driving and electric vehicles are nowadays very active research and development areas. In this paper we present the conversion of a standard Kyburz eRod into an autonomous vehicle that can be operated in challenging environments such as Swiss mountain passes. The overall hardware and software architectures are described in detail with a...

In many unmanned aerial vehicle (UAV) applications, flexible trajectory generation algorithms are required to enable high levels of autonomy for critical mission phases, such as take-off, area coverage, and landing. In this paper, we present a guidance approach which uses the improved intrinsic tau guidance theory to create spatio-temporal 4-D traj...

Selective weed treatment is a critical step in autonomous crop management as related to crop health and yield. However, a key challenge is reliable, and accurate weed detection to minimize damage to surrounding plants. In this paper, we present an approach for dense semantic weed classification with multispectral images collected by a micro aerial...

This paper describes an approach to building a cost-effective and research grade visual-inertial odometry aided vertical taking-off and landing (VTOL) platform. We utilize an off-the-shelf visual-inertial sensor, an onboard computer, and a quadrotor platform that are factory-calibrated and mass-produced, thereby sharing similar hardware and sensor...

Unmanned aerial vehicles (UAVs) and other robots in smart farming applications offer the potential to monitor farm land on a per-plant basis, which in turn can reduce the amount of herbicides and pesticides that must be applied. A central information for the farmer as well as for autonomous agriculture robots is the knowledge about the type and dis...

This paper describes dynamic system identification, and full control of a cost-effective vertical take-off and landing (VTOL) multi-rotor micro-aerial vehicle (MAV) --- DJI Matrice 100. The dynamics of the vehicle and autopilot controllers are identified using only a built-in IMU and utilized to design a subsequent model predictive controller (MPC)...

Background: The EU-project Flourish intends to establish an autonomously operating precision farming system based on the interaction between unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs). For effective mission planning and site-specific ground intervention by the UGV, the growth, mineral nutrition, weed, and health status of t...

Traditional thermoelectric cooling relies on the Peltier effect which produces a temperature drop limited by the figure of merit, zT. This cooling limit is not required from classical thermodynamics but can be traced to problems of thermoelectric compatibility. Alternatively, if a thermoelectric cooler can be designed to achieve full thermoelectric...

The goal of the Flourish project is to bridge the gap between the current and desired capabilities of agricultural robots by developing an adaptable robotic solution for precision farming. Thereby, combining the aerial survey capabilities of a small autonomous multi-copter Unmanned Aerial Vehicle (UAV) with a multipurpose agricultural Unmanned Grou...

Recent developments in Unmanned Aerial Vehicles (UAVs) have made them ideal tools for remotely monitoring agricultural fields. Complementary advancements in computer vision have enabled automated post-processing of images to generate dense 3D reconstructions in the form of point clouds. In this paper we present a monitoring pipeline that uses a rea...

Traditional thermoelectric Peltier coolers exhibit a cooling limit which is primarily determined by the figure of merit, zT. Rather than a fundamental thermodynamic limit, this bound can be traced to the difficulty of maintaining thermoelectric compatibility. Self-compatibility locally maximizes the cooler's coefficient of performance for a given z...