Nino Pereira

Autonomous golf ball picking robot design and development

Purpose – The purpose of this paper is to present the methodology and the results on the design and development of an autonomous, golf ball picking robot, for driving ranges.Design/methodology/approach – The strategy followed to develop a commercial product is presented, based on prior identification requirements, which consist of picking up golf balls on a driving range in a safe and efficient way.Findings – A fully working prototype robot has been developed. It uses two driving wheels and a third cast wheel, and pushes a standard gang which collects the balls from the ground. A hybrid information system was implemented in order to provide a statistically relevant prediction of golf balls location, to optimize the path the robot has to follow in order to reduce time and cost. Autonomous navigation was developed and tested on a simulation environment.Research limitations/implications – Preliminary results showed that the new path planning algorithm Twin‐RRT* is able to form closed loop trajectories and im...

Catadioptric system optimisation for omnidirectional RoboCup MSL robots

Omnidirectional RoboCup MSL robots often use catadioptric vision systems in order to enable 360° of field view. It comprises an upright camera facing a convex mirror, commonly spherical, parabolic or hyperbolic, that reflects the entire space around the robot. This technique is being used for more than a decade and in a similar way by most teams. Teams upgrade their cameras in order to obtain more and better information of the captured area in pixel quantity and quality, but a large image area outside the convex mirror is black and unusable. The same happens on the image centre where the robot shows itself. Some efficiency though, can be improved in this technique by the methods presented in this paper such as developing a new convex mirror and by repositioning the camera viewpoint. Using 3D modelling CAD/CAM software for the simulation and CNC lathe mirror construction, some results are presented and discussed.

High Accuracy Navigation in Unknown Environment Using Adaptive Control

Aiming to reduce cycle time and improving the accuracy on tracking, a modified adaptive control was developed, which adapts autonomously to changing dynamic parameters. The platform used is based on a robot with a vision based sensory system. Goal and obstacles angles are calculated relatively to robot orientation from image processing software. Autonomous robots are programmed to navigate in unknown and unstructured environments where there are multiple obstacles which can readily change their position. This approach underlies in dynamic attractor and repulsive forces. This theory uses differential equations that produce vector fields to control speed and direction of the robot. This new strategy was compared with existing PID method experimentally and it proved to be more effective in terms of behaviour and time-response. Calibration parameters used in PID control are in this case unnecessary. The experiments were carried out in robot Middle Size League football players built for RoboCup. Target pursuit, namely, ball, goal or any absolute position, was tested. Results showed high tracking accuracy and rapid response to moving targets. This dynamic control system enables a good balance between fast movements and smooth behaviour.

Learning Robotics for Youngsters - The RoboParty Experience

The involvement of children and adolescents in robotics is on demand by the many robotics events and competitions all over the world. This non-deterministic world is more attractive, fun, hands-on and with real results than computer virtual simulations and 3D worlds. It is important, by different reasons, to involve people of all ages in an area that some consider the future of mankind and an opportunity to increase the low rate of engineers globally. Robotics competitions at this level are essentially based on teaching motion and programming skills by using Lego™ based robots and a set of challenges to overcome. This paper presents a different approach that is being used by Minho University in order to attract STEM candidates into these fields, with visible success and excellent results. The event is called RoboParty® and teaches children, adolescents and adults, from any area, how to build a robot from scratch, using electronics, mechanics and programming during three non-stop days.

Path planning towards non-compulsory multiple targets using TWIN-RRT*

Purpose The purpose of this paper is to characterise the TWIN-RRT* algorithm which solves a motion planning problem in which an agent has multiple possible targets where none of them is compulsory and retrieves feasible, “low cost”, asymptotically optimal and probabilistically complete paths. The TWIN-RRT* algorithm solves path planning problems for both holonomic and non-holonomic robots with or without kinematic constraints in a 2D environment. Design/methodology/approach It was designed to work equally well with higher degree of freedom agents in different applications. It provides a practical implementation of feasible and fast planning, namely where a closed loop is required. Initial and final configurations are allowed to be exactly the same. Findings The TWIN-RRT* algorithm computes an efficient path for a single agent towards multiple targets where none of them is mandatory. It inherits the low computational cost, probabilistic completeness and asymptotical optimality from RRT*. Research limitations/implications It uses efficiency as cost function, which can be adjusted to the requirements of any given application. TWIN-RRT also shows compliance with kinematic constraints. Practical implications The practical application where this work has been used consists of an autonomous mobile robot that picks up golf balls in a driving range. The multiple targets are the golf balls and the optimum path is a requirement to reduce the time and energy to refill as quickly as possible the balls dispensing machine. Originality/value The new random sampling algorithm – TWIN-RRT* – is able to generate feasible efficient paths towards multiple targets retrieving closed-loop paths starting and finishing at the same configuration.