Policy optimization to learn adaptive motion primitives in path planning with dynamic obstacles

B Angulo, A Panov, K Yakovlev - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
This letter addresses the kinodynamic motion planning for non-holonomic robots in dynamic
environments with both static and dynamic obstacles–a challenging problem that lacks a …

A driver-vehicle model for ADS scenario-based testing

R Queiroz, D Sharma, R Caldas… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Scenario-based testing for automated driving systems (ADS) must be able to simulate traffic
scenarios that rely on interactions with other vehicles. Although many languages for high …

Simultaneous learning and planning in a hierarchical control system for a cognitive agent

AI Panov - Automation and Remote Control, 2022 - Springer
The tasks of behavior planning and decision-making learning in a dynamic environment are
usually divided and considered separately in control systems for intelligent agents. A new …

Одновременное планирование и обучение в иерархической системе управления когнитивным агентом

АИ Панов - Автоматика и телемеханика, 2022 - mathnet.ru
Задачи планирования поведения и обучения принятию решений в динамической среде
в системах управления интеллектуальными агентами обычно разделяют и …

Learning adaptive parking maneuvers for self-driving cars

G Gorbov, M Jamal, AI Panov - International Conference on Intelligent …, 2022 - Springer
This paper addresses the autonomous parking for a vehicle in environments with static and
dynamic obstacles. Although parking maneuvering has reached the level of fully automated …

Toward dynamically scalable open-source motion planning on the mobile edge and in the cloud

E Gallegos - 2023 - ideals.illinois.edu
This work presents a platform capable of deploying massively scalable and portable high
performance software for robotics applications by utilizing containerization technologies. To …