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

TL;DR

This paper introduces a modular safety-control method for mobile robots that uses barrier certificates and a two-layer predictor to effectively avoid obstacles despite time delays, improving response time and safety performance.

Contribution

It presents a scalable, modular safety-control framework combining Smith predictor and barrier certificates, with a two-layer predictor to compensate for time delays in mobile robot control.

Findings

Significantly improves transient response and reduces response time.

Effectively accommodates multiple obstacles with shape and distribution independence.

Validated through extensive experiments demonstrating safety and performance enhancements.

Abstract

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.