4 papers
Dynamic Neural Potential Field: Online Trajectory Optimization in the Presence of Moving Obstacles
Aleksei Staroverov, Muhammad Alhaddad, Aditya Narendra +2
Generalist robot policies must operate safely and reliably in everyday human environments such as homes, offices, and warehouses, where people and objects move unpredictably. We pr…
Maneuver Decision-Making with Trajectory Streams Prediction for Autonomous Vehicles
Mais Jamal, Aleksandr Panov
Decision-making, motion planning, and trajectory prediction are crucial in autonomous driving systems. By accurately forecasting the movements of other road users, the decision-mak…
Model-based Policy Optimization using Symbolic World Model
Andrey Gorodetskiy, Konstantin Mironov, Aleksandr Panov
The application of learning-based control methods in robotics presents significant challenges. One is that model-free reinforcement learning algorithms use observation data with lo…
Neural Potential Field for Obstacle-Aware Local Motion Planning
Muhammad Alhaddad, Konstantin Mironov, Aleksey Staroverov +1
Model predictive control (MPC) may provide local motion planning for mobile robotic platforms. The challenging aspect is the analytic representation of collision cost for the case…