Russia’s ‘Marker’ Robitic Platform Completes 30Km Trek In Autonomous Mode

Support SouthFront

Russia's 'Marker' Robitic Platform Completes 30Km Trek In Autonomous Mode

Click to see full-size image

Russia’s Experimental robotic platform “Marker” completed a trek of approximately 30 kilometers, entirely in autonomous mode, the Advanced Research Fund (FPI) reported on December 30th.

The tests were carried out in the Chelyabinsk region.

The route of the vehicle was laid through an unprepared territory – a forest-steppe with a snow cover.

The autonomous platform motion control system, having received a route assignment with the coordinates of a given point, ensured the platform’s arrival at the finish line in an hour and a half, relying on the data of the technical vision system built on new neural network algorithms.

The autonomous control system of the platform movement provides autonomous laying and adjustment of the route of movement in the event of obstacles – trees, rises, ravines, bushes, etc.

The technical characteristics of the platform provide the possibility of autonomous operation for up to 48 hours on paved roads and up to 24 hours on rough terrain. As part of the next tests, the “Marker” platform will have to cover 50, 100 and 200 kilometers.

The “Marker” experimental robotic platform was developed as part of a project by the Advanced Research Foundation, which was launched in 2018. The goal of the project is to create and conduct a full-scale development of technologies and basic elements of ground-based robotics.

Russia's 'Marker' Robitic Platform Completes 30Km Trek In Autonomous Mode

Click to see full-size image

Reports of the system surfaced back in 2019.

In July, the new Russian combat robot “Marker” in the version on a tracked platform completed movement trials, and in the near future the machine will begin firing practice. This was reported to TASS by the press service of the Advanced Research Fund (FPI).

“Movement trials of the Marker tracked autonomous platform have been completed at the Magnitogorsk test range of robotic systems and complexes. Shooting tests are scheduled for the end of July,” the press service said.

As specified in the fund, the Marker platform was developed and produced by the NPO Androidnaya Tekhnika as part of the first stage of the FPI project.

“The work provides for two types of platforms: tracked and wheeled. Five robotic complexes will be manufactured to test the technologies,” the FPI said.

Earlier, the general director of the FPI, Andrei Grigoriev, said in an interview with TASS that two tracked experimental prototypes of the Marker combat robot had been assembled and were being tested.

The robotic platform “Marker” is a joint project of the Foundation for Advanced Study and NPO “Android Technology” (the developer of the anthropomorphic robot “Fedor”). It is assumed that this combat robot will become the basis for working out the joint interaction of ground robots, unmanned aircraft and special forces. “Marker” is positioned as a constructor for creating models of warfare in the future.

In October 2019, the first open demonstration of the results of the development of the experimental robot “Marker” took place in Magnitogorsk, according to the Foundation for Advanced Research (FPI).

“During the demonstration, the movement of the robotic complex along a given route over rough terrain, autonomous movement with the identification and avoidance of obstacles, autonomous launch of unmanned aerial vehicles from the vehicle’s side were performed,” the FPI said.

During the first phase of the project, two tracked platforms were created for testing ground robotics technologies, equipped with a unified payload module and a cluster launch module for small UAVs.

“Modular solutions, technologies of which are being developed in the course of the project, should provide a new level of unification of the basic elements of robotic systems and the expansion of their functionality,” FPI noted.

The evolution of modern ground-based robotic systems for military purposes is moving towards increasing the ability to perform tasks in an autonomous mode with a gradual decrease in the involvement of the operator in the process of controlling. To increase the level of autonomy of ground-based robotic systems, the development of a number of key technologies is required, which together determine the appearance of promising robotic system. Therefore, it is relevant to develop robotics technologies and bring them to the level of readiness that allows the technologies being created to be applied on promising autonomous robotic systems in real conditions.

To test the technologies being created, to bring their level of readiness, a mobile demonstrator of robotics technologies was created using the modular-modular design principle, with an open information architecture of construction, which provides the possibility of carrying out a full-scale development of technologies and basic elements of ground-based robotics.

The project started in March 2018. Variants of robotic platforms have been worked out, the machines are fully assembled, all architectural solutions for information support have been outlined. Designed and technical solutions and characteristics.

The assessment of the amount of experimental research proposed for testing in the virtual modeling environment and the analysis and justification of the choice of algorithms used in the creation of functional systems is carried out, the justification of the software and hardware architecture is carried out. The composition and technical characteristics of functional systems have been substantiated.

As part of the 1st stage of the project, the assembly and commissioning of two tracked experimental robotic platforms was completed. The machines are equipped with sensor equipment and a set of payload modules.

A functional control system has been created that allows working in a mode close to real time. As part of the development of a group control system, the tasks of automated preparation of a route assignment, laying a route, maintaining formation and avoiding obstacles were solved. Algorithms and software modules have been developed to detect obstacles and targets of various classes.

MORE ON THE TOPIC:

Support SouthFront