CA-HCBF creates a unified acceleration-level safety framework for mixed holonomic and nonholonomic robots and allocates avoidance duties proportionally to each robot's capability using a support-function metric and clipping.
hub
Safety barrier certificates for collisions-free multirobot systems
11 Pith papers cite this work. Polarity classification is still indexing.
11
Pith papers citing it
hub tools
citation-role summary
background 2
citation-polarity summary
roles
background 2polarities
background 2representative citing papers
A new collaborative safety framework for multi-agent systems uses control barrier functions and Hamilton's rule to let agents trade off their own safety for higher-priority neighbors.
Presents a distributed data-driven zeroing control barrier function (3D-ZCBF) framework that derives explicit safety conditions from data to preserve communication network connectivity in leader-follower multi-agent systems.
REACT is a two-layer control system for wheeled mobile robots combining centralized environment-adaptive formation generation with distributed joint spatio-temporal trajectory planning for continuous navigation in complex settings.
FORMULA integrates MPC with CLFs and neural network CBFs for distributed safe formation control in multi-robot systems.
A distributed optimization controller uses truncation functions and two-time-scale auxiliary variables to guarantee collision avoidance, connectivity preservation, and target convergence for multi-agent systems under time-varying communication topologies.
SACBFs guarantee continuous-time safety and finite-time reach-and-remain under zero-order-hold control by estimating inter-sample barrier evolution with Taylor upper bounds and adding a relaxed variant for multiple constraints.
A decentralized control framework using time-varying nonsmooth Lyapunov functions lets each agent satisfy only a local constraint, while the sum still converges, including exact decentralized coverage of time-varying densities.
A real-time PDE-constrained CLF-CBF quadratic program steers multi-robot density for target tracking, obstacle avoidance, and multi-cycle energy sufficiency under localization and motion noise.
A CBF-augmented NMPC framework for two quadrupeds models the robot-payload system as a DAE and enforces collision avoidance in hardware tests under uncertainty.
Decentralized density control for multi-robot systems using PDE-constrained optimization ensures global safety from local constraints with reduced computation and communication needs.
citing papers explorer
-
Capability-Aware Heterogeneous Control Barrier Functions for Decentralized Multi-Robot Safe Navigation
CA-HCBF creates a unified acceleration-level safety framework for mixed holonomic and nonholonomic robots and allocates avoidance duties proportionally to each robot's capability using a support-function metric and clipping.
-
Collaborative Altruistic Safety in Coupled Multi-Agent Systems
A new collaborative safety framework for multi-agent systems uses control barrier functions and Hamilton's rule to let agents trade off their own safety for higher-priority neighbors.
-
A Distributed Framework for Data-Driven Safe Coordination in Leader-Follower Networks
Presents a distributed data-driven zeroing control barrier function (3D-ZCBF) framework that derives explicit safety conditions from data to preserve communication network connectivity in leader-follower multi-agent systems.
-
REACT: Environment-Adaptive Architecture for Continuous Formation Navigation of Wheeled Mobile Robots
REACT is a two-layer control system for wheeled mobile robots combining centralized environment-adaptive formation generation with distributed joint spatio-temporal trajectory planning for continuous navigation in complex settings.
-
FORMULA: FORmation MPC with neUral barrier Learning for safety Assurance
FORMULA integrates MPC with CLFs and neural network CBFs for distributed safe formation control in multi-robot systems.
-
Distributed Safety-Critical Control of Multi-Agent Systems with Time-Varying Communication Topologies
A distributed optimization controller uses truncation functions and two-time-scale auxiliary variables to guarantee collision avoidance, connectivity preservation, and target convergence for multi-agent systems under time-varying communication topologies.
-
Sampling-Aware Control Barrier Functions for Safety-Critical and Finite-Time Constrained Control
SACBFs guarantee continuous-time safety and finite-time reach-and-remain under zero-order-hold control by estimating inter-sample barrier evolution with Taylor upper bounds and adding a relaxed variant for multiple constraints.
-
Disentangled Control of Multi-Agent Systems
A decentralized control framework using time-varying nonsmooth Lyapunov functions lets each agent satisfy only a local constraint, while the sum still converges, including exact decentralized coverage of time-varying densities.
-
Safe and Energy-Aware Multi-Robot Density Control via PDE-Constrained Optimization for Long-Duration Autonomy
A real-time PDE-constrained CLF-CBF quadratic program steers multi-robot density for target tracking, obstacle avoidance, and multi-cycle energy sufficiency under localization and motion noise.
-
Safety-Critical Centralized Nonlinear MPC for Cooperative Payload Transportation by Two Quadrupedal Robots
A CBF-augmented NMPC framework for two quadrupeds models the robot-payload system as a DAE and enforces collision avoidance in hardware tests under uncertainty.
-
Safe Decentralized Density Control of Multi-Robot Systems using PDE-Constrained Optimization with State Constraints
Decentralized density control for multi-robot systems using PDE-constrained optimization ensures global safety from local constraints with reduced computation and communication needs.