Beamforming is an advanced signal processing technique used in sensor arrays for directional signal transmission

or reception. The paper deals with a system based on an ultrasound transmitter and an array of

receivers, to determine the distance to an obstacle by measuring the time of flight and – using the phase

beamforming technique to process the output signals of receivers for finding the direction from which the

reflected signal is received – locates the obstacle. The embedded beam-former interacts with a PID-based

line follower robot to improve performance of the line follower navigation algorithm by detecting and

avoiding obstacles. The PID (proportional-integral-derivative) algorithm is also typically used to control

industrial processes. It calculates the difference between a measured value and a desired set of points, then

attempts to minimize the error by adjusting the output. The overall navigation system combines a PID-based

trajectory follower with a spatial-temporal filter (beamformer) that uses the output of an array of sensors to

extract signals received from an obstacle in a particular direction in order to guide an autonomous vehicle

or a robot along a safe path.

Whatever the type of surgery related to inner organs, traditional or robotic, the contact with them during surgery is a key moment for pursuing the intervention. Contacts by means of surgery instruments namely scalpels, staples, clamps, graspers, etc. are decisive moments. False, and erroneous touching and manoeuvring of organs operated on can cause irreversible damage as regard morphological aspects (outer impact) and physiological aspects (inner impact). The topic is a great challenge in the effort to measure and characterize damages. In general, electrical instruments for surgery employ the following technologies: ultrasound, radiofrequency (monopolar, and bipolar), and laser. They all result in thermal damages difficult to evaluate. The article proposes a method for a pre-screening of organ features during robotic surgery sessions by pointing out mechanical and thermal stresses. A dedicated modelling has been developed based on experimental activities during surgery session. The idea is to model tissue behaviour from real images to help surgeons to be aware of handling during surgery. This is the first step for generalization by considering the type of organ. The measurement acquisitions have been performed by means of an advanced external camera located over the surgery quadrant. The modelling and testing have been carried out on kidneys. The modelling, carried out through Comsol Multiphysics, is based on the bioheat approach. A further comparative technique has been implemented. It is based on computer vision for robotics. The findings of human tissue behavior exhibit reliable results.