ROSYApr 30, 2021

Safety-Control of Mobile Robots Under Time-Delay Using Barrier Certificates and a Two-Layer Predictor

arXiv:2104.15047v1
Originality Incremental advance
AI Analysis

This work addresses safety and agility challenges for autonomous mobile robots in real-time applications, representing an incremental improvement with domain-specific innovations.

The paper tackled the problem of ensuring safe obstacle avoidance for mobile robots under time-delay constraints by proposing a modular safety-control design using barrier certificates and a two-layer predictor, which experimentally improved transient performance and reduced response time.

Performing swift and agile maneuvers is essential for the safe operation of autonomous mobile robots. Moreover, the presence of time-delay restricts the response time of the system and hinders the safety performance. Thus, this paper proposes a modular and scalable safety-control design that utilizes the Smith predictor and barrier certificates to safely and consistently avoid obstacles with different footprints. The proposed solution includes a two-layer predictor to compensate for the time-delay in the servo-system and angle control loops. The proposed predictor configuration dramatically improves the transient performance and reduces response time. Barrier certificates are used to determine the safe range of the robot's heading angle to avoid collisions. The proposed obstacle avoidance technique conveniently integrates with various trajectory tracking algorithms, which enhances design flexibility. The angle condition is adaptively calculated and corrects the robot's heading angle and angular velocity. Also, the proposed method accommodates multiple obstacles and decouples the control structure from the obstacles' shape, count, and distribution. The control structure has only eight tunable parameters facilitating control calibration and tuning in large systems of mobile robots. Extensive experimental results verify the effectiveness of the proposed safety-control.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes