Estimation of the Energy Consumption of an All-Terrain Mobile Manipulator for Operations in Steep Vineyards

A heterogeneous robotic system that can perform various tasks in the steep vineyards of the Mediterranean region was developed and tested as part of the HEKTOR—Heterogeneous Autonomous Robotic System in Viticulture and Mariculture—project. This article describes the design of hardware and an easy-to-use method for evaluating the energy consumption of the system, as well as, indirectly, its deployment readiness level. The heterogeneous robotic system itself consisted of a flying robot—a light autonomous aerial robot (LAAR)—and a ground robot—an all-terrain mobile manipulator (ATMM), composed of an all-terrain mobile robot (ATMR) platform and a seven-degree-of-freedom (DoF) torque-controlled robotic arm. A formal approach to describe the topology and parameters of selected vineyards is presented. It is shown how Google Earth data can be used to make an initial estimation of energy consumption for a selected vineyard. On this basis, estimates of energy consumption were made for the tasks of protective spraying and bud rubbing. The experiments were conducted in two different vineyards, one with a moderate slope and the other with a much steeper slope, to evaluate the proposed estimation method.

Predicting Flying Robot Dynamics with Deep Learning

With the rapid increase in the power of computing and technological advances in robotics, research in the field of robotics has rapidly become very expansive. Being able to accurately predict movements of a robot is vital to many applications within this field, allowing for more precise simulation and prototyping as well as more accurate control of robotic systems. In this paper, we present an adaptable neural network that accurately predicts the movement of quadcopter robotic agents which can be expanded to encompass many more robots and applications given the requisite data, producing accurate results within a small margin for error.

Unmanned Aerial Vehicle Forensic Investigation Process : Dji Phantom 4 Drone as A Case Study

A drone, technological term Unmanned aerial vehicle (UAV), means any aircraft operating or designed to operate autonomously or to be piloted remotely without a pilot on board. Essentially, a drone is a flying robot that can be remotely controlled or fly autonomously through software-controlled flight plans in their embedded systems, working in conjunction with onboard sensors and GPS. The easy accessibility to everyone led to an increase in drone crime. Criminals are using drones in many malicious activities worldwide due to the drones’ ability to offer live-stream, real-time video, and image capture, along with the ability to fly and transport goods. Terrorist groups are using aerial drones to conduct and coordinate attacks. Forensic laboratories have been receiving Drone cases throughout India. The drone has been built that can be operated by a radio frequency controller and send live audio-visual feedback. This paper aims to provide a case study of Drone, DJI Phantom 4 and presents the acquisition, examination, analysis of important artifacts recorded flight data and discuss some possible data extractions from its flash memory, GPS (navigator) & SD card.