Asymmetric Design of Control Barrier Function for Multiagent Autonomous Robotic Systems

In this paper, we propose a method to avoid "no-solution" situations of the control barrier function (CBF) for distributed collision avoidance in a multiagent autonomous robotic system (MARS). MARS, which is composed of distributed autonomous mobile robots, is expected to effectively perform cooperative tasks such as searching in a certain area. Therefore, collision avoidance must be considered when implementing MARS in the real world. The CBF is effective for solving collision-avoidance problems. However, in extreme conditions where many robots congregate at one location, the CBF constraints that ensure a safe distance between robots may be violated. We theoretically demonstrate that this problem can occur in certain situations, and introduce an asymmetric design for the inequality constraints of CBF. We asymmetrically decentralized inequality constraints with weight functions using the absolute speed of the robot so that other robots can take over the constraints of the robot in severe condition. We demonstrate the effectiveness of the proposed method in a two-dimensional situation wherein multiple robots congregate at one location. We implement the proposed method on real robots and the confirmed the effectiveness of this theory

Wave-Type Interaction within a Robotic Swarm System for Decentralized Estimation of Global Geometric States

For a robotic swarm system composed of autonomous mobile robots, controlling and using asymmetric global geometric states promotes the task performance of the swarm. This paper presents a systematic method for estimating asymmetric global geometric states over a swarm system. To overcome the limitations of local observation or communication ability, we propose a wave-type interaction among neighboring robots. We assume that each robot has a scalar state variable called a phase, which is manipulated through interactions. Through the analysis of eigenvalues of a graph Laplacian matrix corresponding to a local communication network of robots, we show that a robot can estimate global states, such as the size of an entire swarm, by frequency analysis of its phase. We also analyzed the stability of the wave-type interaction based on von-Neumann stability. We verified the proposed method by computer simulations, in which robots in a swarm detected the deformation in the shape of the swarm when the swarm was passing through a narrow area. The result will contribute to building a control system for swarms that can manipulate their shape or characteristics to adapt themselves based on tasks or environmental requirements

Control Input Design for a Robot Swarm Maintaining Safety Distances in Crowded Environment

We consider an autonomous and decentralized mobile robotic swarm that does not require an advanced communication system; moreover, each robot must pass a narrow space preserving the distance with other robots. The control barrier function (CBF) method is useful for robotic swarms to guarantee collision avoidance. However, introducing CBF inequalities can cancel other objectives and sometimes causes a deadlock problem. Therefore, we introduce a coupled oscillator system to generate asymmetric global order by itself to avoid deadlock. By generating an effective global order in the swarm, each robot adequately moves to a target position without requiring high-cost communication systems