Frontier Based Exploration for Autonomous Robot

2018/06/10 by Anirudh Topiwala, Topiwala, Anirudh, Pranav Inani +3 · 7 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization

paper · pdf · doi:10.48550/arxiv.1806.03581

openalex publication_date 2018/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Exploration is process of selecting target points that yield the biggest contribution to a specific gain function at an initially unknown environment. Frontier-based exploration is the most common approach to exploration, wherein frontiers are regions on the boundary between open space and unexplored space. By moving to a new frontier, we can keep building the map of the environment, until there are no new frontiers left to detect. In this paper, an autonomous frontier-based exploration strategy, namely Wavefront Frontier Detector (WFD) is described and implemented on Gazebo Simulation Environment as well as on hardware platform, i.e. Kobuki TurtleBot using Robot Operating System (ROS). The advantage of this algorithm is that the robot can explore large open spaces as well as small cluttered spaces. Further, the map generated from this technique is compared and validated with the map generated using turtlebot_teleop ROS Package.

Cited by

• ImagineNav++: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination
• PanoNav: Mapless Zero-Shot Object Navigation with Panoramic Scene Parsing and Dynamic Memory
• Zero-shot Structure Learning and Planning for Autonomous Robot Navigation using Active Inference
• Bio-Inspired Topological Autonomous Navigation with Active Inference in Robotics
• Navigation and Exploration with Active Inference: from Biology to Industry
• History-Augmented Vision-Language Models for Frontier-Based Zero-Shot Object Navigation
• Auxiliary Heuristics for Frontier Based Planners

Related

• Ada-Detector: Adaptive Frontier Detector for Rapid Exploration
• Reinforcement Learning with Frontier-Based Exploration via Autonomous Environment
• FrontierNet: Learning Visual Cues to Explore
• FH-DRL: Exponential-Hyperbolic Frontier Heuristics with DRL for accelerated Exploration in Unknown Environments
• HPHS: Hierarchical Planning based on Hybrid Frontier Sampling for Unknown Environments Exploration