Abstract
Manufacturing and production industries are increasingly turning to robots to carry out repetitive picking operations in an efficient manner. This paper focuses on tackling the novel challenge of automating the bin picking process for entangled objects, for which there is very little research. The chosen case study are sets of freely curved tubes, which are prone to occlusions and entanglement. The proposed algorithm builds a representation of the tubes as an ordered list of cylinders and joints using a point cloud acquired by a 3D scanner. This representation enables the detection of occlusions in the tubes. The solution also performs grasp planning and motion planning, by evaluating post-grasp trajectories via simulation using Gazebo and the ODE physics engine. A force/torque sensor is used to determine how many items were picked by a robot gripper and in which direction it should rotate to solve cases of entanglement. Real-life experiments with sets of PVC tubes and rubber radiator hoses showed that the robot was able to pick a single tube on the first try with success rates of 99% and 93%, respectively. This study indicates that using simulation for motion planning is a promising solution to deal with entangled objects.

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Throughout this paper, the model, its parameter estimation and a controller for a solution using a DC motor with a gearbox worm, coupled to a non-rigid joint, will be presented. First, the modeling of a non-linear system based on a DC Motor with Worm Gearbox coupled to a non-rigid joint is presented. The full system was modeled based on the modeling of two sub-systems that compose it - a non-rigid joint configuration and the DC motor with the worm gearbox configuration. Despite the subsystems are interdependent, its modelling can be performed independently trough a carefully chosen set of experiments. Modeling accurately the system is crucial in order to simulate and know the expected performance. The estimation process and the proposed experimental setup are presented. This setup collects data from an absolute encoder, a load cell, voltage and current sensors. The data obtained from these sensors is presented and used to obtaining some physical parameters from both systems. Finally, through an optimization process, the remaining parameters are estimated, thus obtaining a realistic model of the complete system. Finally, the controller setup is presented and the results obtained are also presented.

Abstract
Ultrasonic sensors offers attractive features at an affordable cost. The main problem faced by the use of these devices is that the data obtained are not so easy to interpret, restricting their efficiency. This paper describes a binaural sensor system that is able to determine the coordinates of an object or a target in a two-dimensional space, focusing on mathematical and signal processing techniques to provide accurate measurements and increase the system reliability. The proposed work consists only of low cost components, which aims to demonstrate that improvement is possible. Experimental tests, performed in different scenarios, reported good accuracy and repeatability of the measurements. © 2020, Springer Nature Switzerland AG.