2 citations · 5 across the 12 of their papers we have counts for
13 papers
Belief-Informed Hybrid Control with Almost-Sure Target-Set Convergence
Clinton Enwerem, Saleh Kemal, John S. Baras +1
Controlling a hybrid system to a target set under parameter uncertainty can require informative actions that temporarily drive the system state away from the specified set. We prop…
Grasp Execution Without a Planner: Configuration-Space Grasp Distance Fields with Certified Safety & Guaranteed Quality
Clinton Enwerem, John S. Baras, Calin Belta
Mainstream plan-then-track approaches to multifingered grasp execution entail selecting a grasp, planning a collision-free trajectory, and tracking the resulting trajectory via a f…
FIRMGrasp: A Friction-Informed Risk Margin for Robust Grasp Synthesis
Clinton Enwerem, John S. Baras, Calin Belta
Classical grasp quality metrics assume one deterministic friction coefficient and therefore cannot assess whether a grasp maintains force closure across plausible friction values.…
EquiDexFlow: Contact-Grounded SE(3)-Equivariant Dexterous Grasp Generative Flows
Clinton Enwerem, John S. Baras, Calin Belta
Most learned dexterous grasp generators relegate contact forces to a downstream verification step, so a kinematically-plausible pose can still violate the conditions for a stable p…
IDDMBSE: Integrating Data-Driven and Model-Based Systems Engineering for Trusted Autonomous Cyber-Physical Systems
John S. Baras, Sai Sandeep Damera, Ryan Matheu +2
Autonomous cyber-physical systems (CPS) sit at the intersection of Model-Based Systems Engineering (MBSE) and data-driven Machine Learning and Artificial Intelligence (ML/AI), yet…
Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty
Clinton Enwerem, Shreya Kalyanaraman, John S. Baras +1
Contact variability, sensing uncertainty, and external disturbances make grasp execution stochastic. Expected-quality objectives ignore tail outcomes and often select grasps that f…
Risk-Constrained Belief-Space Optimization for Safe Control under Latent Uncertainty
Clinton Enwerem, John S. Baras, Calin Belta
Many safety-critical control systems operate under latent uncertainty that sensors cannot resolve at decision time. Such uncertainty, arising from unknown physical properties, dist…
Safety-Aware Reinforcement Learning for Control via Risk-Sensitive Action-Value Iteration and Quantile Regression
Clinton Enwerem, Aniruddh G. Puranic, John S. Baras +1
Mainstream approximate action-value iteration reinforcement learning (RL) algorithms suffer from overestimation bias, leading to suboptimal policies in high-variance stochastic env…
Robust Stochastic Shortest-Path Planning via Risk-Sensitive Incremental Sampling
Clinton Enwerem, Erfaun Noorani, John S. Baras +1
With the pervasiveness of Stochastic Shortest-Path (SSP) problems in high-risk industries, such as last-mile autonomous delivery and supply chain management, robust planning algori…
Safe Collective Control under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions
Clinton Enwerem, John S. Baras
We consider the problem of safely coordinating ensembles of identical autonomous agents to conduct complex missions with conflicting safety requirements and under noisy control inp…
Consensus-Based Leader-Follower Formation Tracking for Control-Affine Nonlinear Multiagent Systems
Clinton Enwerem, John S. Baras
In the typical multiagent formation tracking problem centered on consensus, the prevailing assumption in the literature is that the agents' nonlinear models can be approximated by…
Distributed Optimal Formation Control for an Uncertain Multiagent System in the Plane
Clinton Enwerem, John Baras, Danilo Romero
In this paper, we present a distributed optimal multiagent control scheme for quadrotor formation tracking under localization errors. Our control architecture is based on a leader-…
Optimal Controller Tuning Technique for a First-Order Process with Time Delay
Clinton Enwerem, Ihechiluru Okoro
We present a controller tuning strategy for first-order plus time delay (FOPTD) processes, where the time delay in the model is approximated using the Padé function. Using Routh-Hu…