activity
20182026
most citedSearch-based optimal motion planning for automated driving

86 citations · 92 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Online Generation of Collision-Free Trajectories in Dynamic Environments

Nermin Covic, Bakir Lacevic

In this paper, we present an online method for converting an arbitrary geometric path, represented by a sequence of states, and generated by any planner (e.g., sampling-based plann…

cs.RO2025

Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives

Benjamin Kraljusic, Zlatan Ajanovic, Nermin Covic +1

This work proposes a motion planning algorithm for robotic manipulators that combines sampling-based and search-based planning methods. The core contribution of the proposed approa…

cs.RO2025★ 1 cited

Real-Time Sampling-Based Safe Motion Planning for Robotic Manipulators in Dynamic Environments

Nermin Covic, Bakir Lacevic, Dinko Osmankovic +1

In this paper, we present the main features of Dynamic Rapidly-exploring Generalized Bur Tree (DRGBT) algorithm, a sampling-based planner for dynamic environments. We provide a det…

cs.AI2024

SLOPE: Search with Learned Optimal Pruning-based Expansion

Davor Bokan, Zlatan Ajanovic, Bakir Lacevic

Heuristic search is often used for motion planning and pathfinding problems, for finding the shortest path in a graph while also promising completeness and optimal efficiency. The…

cs.RO2022★ 3 cited

Octocopter Design: Modelling, Control and Motion Planning

Nedim Osmic, Adnan Tahirovic, Bakir Lacevic

This book provides a solution to the control and motion planning design for an octocopter system. It includes a particular choice of control and motion planning algorithms which is…

cs.LG2019★ 1 cited

A novel approach to model exploration for value function learning

Zlatan Ajanovic, Halil Beglerovic, Bakir Lacevic

Planning and Learning are complementary approaches. Planning relies on deliberative reasoning about the current state and sequence of future reachable states to solve the problem.…

cs.LG2018★ 1 cited

Safe learning-based optimal motion planning for automated driving

Zlatan Ajanovic, Bakir Lacevic, Georg Stettinger +2

This paper presents preliminary work on learning the search heuristic for the optimal motion planning for automated driving in urban traffic. Previous work considered search-based…

cs.RO2018★ 86 cited

Search-based optimal motion planning for automated driving

Zlatan Ajanovic, Bakir Lacevic, Barys Shyrokau +2

This paper presents a framework for fast and robust motion planning designed to facilitate automated driving. The framework allows for real-time computation even for horizons of se…