Construction and development of an automatic sprayer for greenhouse

Abstract: This paper presents design and construction of an autonomous robot for using in greenhouse condition.  The robot designed to prevent human hazards involved in spraying potentially toxic chemicals in the confined space of a hot and steamy glasshouse.  In order to navigate the robot, hot water piping rails along the rows were used as a method of guidance for autonomous robot.  The robot is able to force and back along the hot water piping rails of rows in greenhouse avoiding the expensive and complicated navigation systems.  Power was transmitted from two DC motors to two driving wheels through a gearbox and shaft system.  The AVR microcontroller controls all of the inputs and outputs of the system.  To program the micro used from BASCOM-AVR version 1.11.9.8 and for circuit simulating used from PROTEUS 7 professional.  The obtained Results indicated that the robot is capable to cover more than 90% of surface which needed to spray.   Keywords: Autonomous robot, human hazards, design, spraying, greenhouse, AVR Microcontrolle

Plume Analysis and Detection

This work involves the design and implementation of a gas-sensing mobile robot as an experimental tool to reconstruct a carbon dioxide plume in real-time based on concentration gradient and local wind speed measurements. The autonomous robot, an iRobot Create 2, achieves navigation through an embedded micro-controller using on-board sensors and various sensor fusion methods. A mass flow controller and diffuser are used to dependably generate a plume that simulates a point source. A base station reconstructs the plume via a state estimator through data from the robot and transmits commands to guide it into spatial regions of interest. This method has applicability for unmanned vehicles tracking emissions of contaminants and their effects in the environment

Development of a bio-inspired vision system for mobile micro-robots

In this paper, we present a new bio-inspired vision system for mobile micro-robots. The processing method takes inspiration from vision of locusts in detecting the fast approaching objects. Research suggested that locusts use wide field visual neuron called the lobula giant movement detector to respond to imminent collisions. We employed the locusts' vision mechanism to motion control of a mobile robot. The selected image processing method is implemented on a developed extension module using a low-cost and fast ARM processor. The vision module is placed on top of a micro-robot to control its trajectory and to avoid obstacles. The observed results from several performed experiments demonstrated that the developed extension module and the inspired vision system are feasible to employ as a vision module for obstacle avoidance and motion control

Validated reduced order models for simulating trajectories of bio-inspired artificial micro-swimmers

Autonomous micro-swimming robots can be utilized to perform specialized procedures such as in vitro or in vivo medical tasks as well as chemical surveillance or micro manipulation. Maneuverability of the robot is one of the requirements that ensure successful completion of its task. In micro fluidic environments, dynamic trajectories of active micro-swimming robots must be predicted reliably and the response of control inputs must be well-understood. In this work, a reduced-order model, which is based on the resistive force theory, is used to predict the transient, coupled rigid body dynamics and hydrodynamic behavior of bio-inspired artificial micro-swimmers. Conceptual design of the micro-swimmer is biologically inspired: it is composed of a body that carries a payload, control and actuation mechanisms, and a long flagellum either such as an inextensible whip like tail-actuator that deforms and propagates sinusoidal planar waves similar to spermatozoa, or of a rotating rigid helix similar to many bacteria, such as E. Coli. In the reduced-order model of the microswimmer, fluid’s resistance to the motion of the body and the tail are computed from resistive force theory, which breaks up the resistance coefficients to local normal and tangential components. Using rotational transformations between a fixed world frame, body frame and the local Frenet-Serret coordinates on the helical tail we obtain the full 6 degrees-of-freedom relationship between the resistive forces and torques and the linear and rotational motions of the swimmer. In the model, only the tail’s frequency (angular velocity for helical tail) is used as a control input in the dynamic equations of the micro-swimming robot. The reduced-order model is validated by means of direct observations of natural micro swimmers presented earlier in the literature and against; results show very good agreement. Three-dimensional, transient CFD simulations of a single degree of freedom swimmer is used to predict resistive force coefficients of a micro-swimmer with a spherical body and flexible tail actuator that uses traveling plane wave deformations for propulsion. Modified coefficients show a very good agreement between the predicted and actual time-dependent swimming speeds, as well as forces and torques along all axes

Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design and software architecture of our proposed solution, and showcase how all the distinct components can be integrated to enable smooth robot operation. We provide critical insight on hardware and software component selection and development, and present results from extensive experimental testing in real-world warehouse environments. Experimental testing reveals that our proposed solution can deliver fast and robust aerial robot autonomous navigation in cluttered, GPS-denied environments.Comment: Pre-peer reviewed version of the article accepted in Journal of Field Robotic

SPRK: A Low-Cost Stewart Platform For Motion Study In Surgical Robotics

To simulate body organ motion due to breathing, heart beats, or peristaltic movements, we designed a low-cost, miniaturized SPRK (Stewart Platform Research Kit) to translate and rotate phantom tissue. This platform is 20cm x 20cm x 10cm to fit in the workspace of a da Vinci Research Kit (DVRK) surgical robot and costs $250, two orders of magnitude less than a commercial Stewart platform. The platform has a range of motion of +/- 1.27 cm in translation along x, y, and z directions and has motion modes for sinusoidal motion and breathing-inspired motion. Modular platform mounts were also designed for pattern cutting and debridement experiments. The platform's positional controller has a time-constant of 0.2 seconds and the root-mean-square error is 1.22 mm, 1.07 mm, and 0.20 mm in x, y, and z directions respectively. All the details, CAD models, and control software for the platform is available at github.com/BerkeleyAutomation/sprk