Safe Learning-Based Control
Preventing unconstrained CBF safety filters caused by incorrect relative degree assumptions
Addressing relative degree issues in control barrier function synthesis with physics-informed neural networks
Advancing reproducibility, benchmarks, and education with remote sim2real
Practical considerations for discrete-time implementations of continuous-time control barrier function-based safety filters
Optimized control invariance conditions for uncertain input-constrained nonlinear control systems
Is data all that matters? The role of control frequency for learning-based sampled-data control of uncertain systems
What is the impact of releasing code with publications? Statistics from the machine learning, robotics, and control communities
Robust predictive output-feedback safety filter for uncertain nonlinear control systems
Barrier Bayesian linear regression: online learning of control barrier conditions for safety-critical control of uncertain systems
Safe learning in robotics: from learning-based control to safe reinforcement learning
safe-control-gym: a unified benchmark suite for safe learning-based control and reinforcement learning
Bridging the model-reality gap with Lipschitz network adaptation
RLO-MPC: Robust learning-based output feedback MPC for improving the performance of uncertain systems in iterative tasks
Learning to fly: a Gym environment with pybullet physics for reinforcement learning of multi-agent quadcopter control
Deep neural networks as add-on modules for enhancing robot performance in impromptu trajectory tracking
An analysis of the expressiveness of deep neural network architectures based on their lipschitz constants
Active training trajectory generation for inverse dynamics model learning with deep neural networks
An inversion-based learning approach for improving impromptu trajectory tracking of robots with non-minimum phase dynamics
Design of deep neural networks as add-on blocks for improving impromptu trajectory tracking
Deep neural networks as add-on modules for high-accuracy impromptu trajectory tracking
A comparison of probabilistic population code and sampling-based code in neural state
estimations
Perceptive and Semantic Safety
Where did I leave my glasses? Open-vocabulary semantic exploration in real-world semi-static environments
SM2ITH: safe mobile manipulation with interactive human prediction via task-hierarchical bilevel model predictive control
Semantically safe robot manipulation: from semantic scene understanding to motion safeguards
Perception-based hierarchical-task MPC for sequential mobile manipulation in unstructured semi-static environments
Hierarchical task model predictive control for sequential mobile manipulation tasks
Closing the perception-action loop for semantically safe navigation in semi-static environments
Control-barrier-aided teleoperation with visual-inertial SLAM for safe MAV navigation in complex environments
Fly out the window: exploiting discrete-time flatness for fast vision-based multirotor flight
Multiagent Coordination
SwarmGPT: combining large language models with safe motion planning for drone swarm choreography
Safe multi-agent reinforcement learning for behavior-based cooperative navigation
AMSwarmX: Safe swarm coordination in CompleX environments via implicit non-convex decomposition of the obstacle-free space
AMSwarm: an alternating minimization approach for safe motion planning of quadrotor swarms in cluttered environments
Experience selection using dynamics similarity for efficient multi-source transfer learning between robots
To share or not to share? Performance guarantees and the asymmetric nature of cross-robot experience transfer
Knowledge transfer between robots with similar dynamics for high-accuracy impromptu trajectory tracking