Autonomous Vehicle Navigation
DOI: 10.1201/b19544
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Summary
This book, authored by Lounis Adouane, addresses the challenge of achieving safe, flexible, and reliable autonomous navigation for mobile robots and vehicles in complex, cluttered, and dynamic environments. The work is motivated by the limitations of traditional control architectures, particularly the lack of analytic stability guarantees in purely reactive behavioral systems and the computational rigidity of fully cognitive planning. The primary objective is to develop generic multi-controller architectures that decompose complex navigation tasks into reliable elementary controllers—such as obstacle avoidance and target tracking—while ensuring smooth coordination and stability through Lyapunov-based synthesis. The methodology progresses from behavioral to hybrid architectures. Chapter 2 introduces a reactive obstacle avoidance controller based on Parallel Elliptic Limit-Cycles (PELC), which allows robots to navigate around obstacles using homogeneous set-points. Chapter 3 develops HybridCD (Continuous/Discrete) architectures that integrate stable control laws for target reaching and tracking, utilizing adaptive functions and gains to ensure smooth switching between controllers. Chapter 4 presents HybridRC (Reactive/Cognitive) architectures, which dynamically switch between reactive navigation and cognitive planning (using global PELC-based path generation) based on environmental uncertainty. Chapter 5 proposes a navigation strategy based on sequential target reaching via optimal waypoint configuration, utilizing an Optimal Multi-criteria Waypoint Selection based on Expanding Tree (OMWS-ET) algorithm to reduce computational costs compared to traditional trajectory following. Chapter 6 extends these concepts to cooperative multi-robot systems, detailing stable formation control using both virtual structure and leader-follower approaches with dynamic constrained set-points. The findings demonstrate the efficacy of these architectures through extensive simulations and experimental validations on various platforms, including Khepera mini-robots, Pioneer robots, and the VIPALAB electric vehicle. Results show that the PELC-based obstacle avoidance ensures safe navigation in cluttered spaces, while the HybridCD and HybridRC architectures provide stable transitions between control modes without inducing oscillations. The OMWS-ET algorithm generates efficient waypoint sets that outperform Voronoï and RRT* methods in terms of path length and safety margins. Furthermore, the cooperative control strategies successfully maintain formation shapes and handle reconfigurations and obstacle avoidance in multi-robot scenarios, with Lyapunov functions confirming the stability of the systems. The significance of this work lies in its contribution to the field of autonomous robotics by bridging the gap between reactive and cognitive control. By providing analytic stability proofs for multi-controller architectures, the book offers a robust framework for deploying autonomous vehicles in real-world applications such as transportation and logistics. The proposed methods enhance autonomy by allowing systems to adapt to dynamic environments while maintaining rigorous safety and reliability standards, addressing critical challenges in the development of fully autonomous mobile robots.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-25 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-26 |
| chunk | success | chunk | — | — | 1 | 2026-06-26 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-26 |
| enrich | success | openalex | — | — | 1 | 2026-06-26 |
| promote | success | — | — | — | 1 | 2026-06-25 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-26 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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