WEBVTT 00:00.530 --> 00:01.880 Hi robotic enthusiast. 00:02.390 --> 00:05.600 At this point in the course, I want to congratulate you. 00:05.720 --> 00:13.370 We have already covered several complex topics and mastered numerous complex concepts in the robotics 00:13.370 --> 00:14.240 industry. 00:14.720 --> 00:21.230 We have also created a software infrastructure that allows us to develop and test new applications for 00:21.230 --> 00:22.610 our robot with ease. 00:23.210 --> 00:30.110 Let's quickly recap the software components we have implemented so far in the course to understand how 00:30.110 --> 00:35.840 to use them to integrate all the exciting new functionalities we have in mind for our robotic arm. 00:36.760 --> 00:44.590 We started by creating a robot simulator using a software that simulates the physical laws and interaction, 00:44.590 --> 00:47.740 replicating the behavior of the real robot on our PC. 00:48.550 --> 00:56.110 Then, using the Ros2 Control library, we developed a control system that receives trajectories and 00:56.110 --> 00:57.610 activates the robot's joint. 00:57.610 --> 01:03.310 Accordingly, by sending position command to the robot's motor to follow those trajectories. 01:03.980 --> 01:10.460 Thanks to the modularity of Ros two and the Ros two Control library, we can use the same control system 01:10.460 --> 01:14.340 developed for the simulated robot also in the real case. 01:14.360 --> 01:18.230 By simply changing the communication interface with the robot's hardware. 01:19.220 --> 01:25.790 Once we were able to activate the robot's joint and move it in the space, we realized how difficult 01:25.790 --> 01:31.490 it is to perform even the simplest pick and place operation with such a control system. 01:32.070 --> 01:37.770 We found it challenging to predict the movements of the robot gripper in the three dimensional space. 01:37.770 --> 01:44.670 When we change the position of one of the robot's joints due to the increasing complexity of the inverse 01:44.670 --> 01:45.930 kinematics problem. 01:46.600 --> 01:53.710 For this reason, we used another incredible open source software available in Ros2 called Moovit to. 01:54.680 --> 02:01.430 Finally, with this tool, we can think directly in Cartesian terms, which is more convenient and familiar 02:01.430 --> 02:06.260 to us, and we can then move and control the position of the robot gripper directly. 02:07.260 --> 02:13.260 The calculation of the angles and the position of each joint and motor that brings the robot's gripper 02:13.260 --> 02:19.410 to the desired position is transparently handled by the moving kinematic solvers. 02:20.140 --> 02:26.980 In addition to all the other features offered by Moovit, this software also provides various interfaces 02:26.980 --> 02:33.580 for interacting with the robot, developing complex applications and integrating with other software. 02:34.330 --> 02:38.140 The first interface that it offers is the graphical interface. 02:38.140 --> 02:45.490 By using Aavs, which offers the users a quick and intuitive way to move the robot plan and execute 02:45.490 --> 02:48.640 trajectories, avoid obstacles and much more. 02:49.500 --> 02:56.400 The second, perhaps more interesting and exciting interface is the one that Moovit provides to other 02:56.400 --> 03:00.270 softwares to other applications through its APIs. 03:01.090 --> 03:08.230 API stands for application programming interface, and it refers to the software interface that move. 03:08.230 --> 03:14.650 It offers to other software, allowing them to exploit moved functionalities at their convenience. 03:15.310 --> 03:21.850 Just as the GUI is a graphical interface provided by Moovit for humans to use its features. 03:21.880 --> 03:27.520 The APIs are an interface that allows other software to use its features. 03:28.310 --> 03:31.940 The implication of this, as you can imagine, are endless. 03:31.970 --> 03:38.810 It is only limited by your imagination and creativity to think of an application that can move the robot 03:38.840 --> 03:41.660 using all the functionalities offered by Moovit. 03:41.840 --> 03:49.040 For example, we can train a neural network to recognize objects to be grasped, or an artificial intelligence 03:49.040 --> 03:55.910 to replace humans in handling the robot, or even create a web application to remotely access the robot. 03:55.940 --> 03:58.100 The possibilities are limitless. 03:58.610 --> 04:06.530 In this course, we will use this API to develop a voice interface with the robot using the Amazon Alexa 04:06.530 --> 04:07.400 Assistant. 04:08.020 --> 04:14.020 It will interpret our voice commands and will translate them into actions for the robot.