6 papers
Predicted-Flow Control Barrier Functions for Non-Control-Affine Systems
Amirsaeid Safari, Jesse B. Hoagg
Control barrier functions (CBFs) enforce safety through conditions imposed pointwise in time without consideration of state evolution over a future horizon. Thus, CBF-based control…
Predicted-Flow Control Barrier Functions for Real-Time Safe Optimal Control
Amirsaeid Safari, Jesse B. Hoagg
Control barrier functions (CBFs) provide real-time safety guarantees through pointwise conditions on the state. However, synthesizing a valid CBF is difficult and the resulting con…
Safe Navigation in Unmapped Environments for Robotic Systems with Input Constraints
Amirsaeid Safari, Jesse B. Hoagg
This paper presents an approach for navigation and control in unmapped environments under input and state constraints using a composite control barrier function (CBF). We consider…
Time-Varying Soft-Maximum Barrier Functions for Safety in Unmapped and Dynamic Environments
Amirsaeid Safari, Jesse B. Hoagg
We present a closed-form optimal feedback control method that ensures safety in an a prior unknown and potentially dynamic environment. This article considers the scenario where lo…
Safe Exploration in Reinforcement Learning: Training Backup Control Barrier Functions with Zero Training Time Safety Violations
Pedram Rabiee, Amirsaeid Safari
This paper introduces the reinforcement learning backup shield (RLBUS), an algorithm that guarantees safe exploration in reinforcement learning (RL) by incorporating backup control…
Time-Varying Soft-Maximum Control Barrier Functions for Safety in an A Priori Unknown Environment
Amirsaeid Safari, Jesse B. Hoagg
This paper presents a time-varying soft-maximum composite control barrier function (CBF) that can be used to ensure safety in an a priori unknown environment, where local perceptio…