arXiv subjects

Aleksandr Sidorenko

Publications and source records attributed to Aleksandr Sidorenko.

3 recordsLinked to original sources

arXiv2026

Learning-Based Strategy for Composite Robot Assembly Skill Adaptation

Contact-rich robotic skills remain challenging for industrial robots due to tight geometric tolerances, frictional variability, and uncertain contact dynamics, particularly when using position-controlled manipulators. This paper presents a reusable and encapsulated skill-based strategy for peg-in-hole assembly, in which adaptation is achieved through Residual Reinforcement Learning (RRL). The assembly process is represented using composite skills with explicit pre-, post-, and invariant conditions, enabling modularity, reusability, and well-defined execution semantics across task variations. Safety and sample efficiency are promoted through RRL by restricting adaptation to residual refinements within each skill during contact-rich interactions, while the overall skill structure and execution flow remain invariant. The proposed approach is evaluated in MuJoCo simulation on a UR5e robot equipped with a Robotiq gripper and trained using SAC and JAX. Results demonstrate that the proposed formulation enables robust execution of assembly skills, highlighting its suitability for industrial automation.

cs.RO↗

arXiv2024

Skills Composition Framework for Reconfigurable Cyber-Physical Production Modules

While the benefits of reconfigurable manufacturing systems (RMS) are well-known, there are still challenges to their development, including, among others, a modular software architecture that enables rapid reconfiguration without much reprogramming effort. Skill-based engineering improves software modularity and increases the reconfiguration potential of RMS. Nevertheless, a skills' composition framework with a focus on frequent and rapid software changes is still missing. The Behavior trees (BTs) framework is a novel approach, which enables intuitive design of modular hierarchical control structures. BTs have been mostly explored from the AI and robotics perspectives, and little work has been done in investigating their potential for composing skills in the manufacturing domain. This paper proposes a framework for skills' composition and execution in skill-based reconfigurable cyber-physical production modules (RCPPMs). It is based on distributed BTs and provides good integration between low-level devices' specific code and AI-based task-oriented frameworks. We have implemented the provided models for the IEC 61499-based distributed automation controllers to show the instantiation of the proposed framework with the specific industrial technology and enable its evaluation by the automation community.

cs.SE↗

arXiv2024

Towards Using Behavior Trees in Industrial Automation Controllers

The Industry 4.0 paradigm manifests the shift towards mass customization and cyber-physical production systems (CPPS) and sets new requirements for industrial automation software in terms of modularity, flexibility, and short development cycles of control programs. Though programmable logical controllers (PLCs) have been evolving into versatile and powerful edge devices, there is a lack of PLC software flexibility and integration between low-level programs and high-level task-oriented control frameworks. Behavior trees (BTs) is a novel framework, which enables rapid design of modular hierarchical control structures. It combines improved modularity with a simple and intuitive design of control logic. This paper proposes an approach for improving the industrial control software design by integrating BTs into PLC programs and separating hardware related functionalities from the coordination logic. Several strategies for integration of BTs into PLCs are shown. The first two integrate BTs with the IEC 61131 based PLCs and are based on the use of the PLCopen Common Behavior Model. The last one utilized event-based BTs and shows the integration with the IEC 61499 based controllers. An application example demonstrates the approach. The paper contributes in the following ways. First, we propose a new PLC software design, which improves modularity, supports better separation of concerns, and enables rapid development and reconfiguration of the control software. Second, we show and evaluate the integration of the BT framework into both IEC 61131 and IEC 61499 based PLCs, as well as the integration of the PLCopen function blocks with the external BT library. This leads to better integration of the low-level PLC code and the AI-based task-oriented frameworks. It also improves the skill-based programming approach for PLCs by using BTs for skills composition.

cs.SE↗