202 citations · 563 across the 65 of their papers we have counts for
68 papers
Safe Planning in Unknown Environments Using Conformalized Semantic Maps
David Smith Sundarsingh, Yifei Li, Tianji Tang +3
This paper addresses semantic planning problems in unknown environments under perceptual uncertainty. The environment contains multiple unknown semantically labeled regions or obje…
PKF: Probabilistic Data Association Kalman Filter for Multi-Object Tracking
Hanwen Cao, George J. Pappas, Nikolay Atanasov
In this paper, we derive a new Kalman filter with probabilistic data association between measurements and states. We formulate a variational inference problem to approximate the po…
Learning to Identify Graphs from Node Trajectories in Multi-Robot Networks
Eduardo Sebastian, Thai Duong, Nikolay Atanasov +2
The graph identification problem consists of discovering the interactions among nodes in a network given their state/feature trajectories. This problem is challenging because the b…
Continuity and Boundedness of Minimum-Norm CBF-Safe Controllers
Mohammed Alyaseen, Nikolay Atanasov, Jorge Cortes
The existence of a Control Barrier Function (CBF) for a control-affine system provides a powerful design tool to ensure safety. Any controller that satisfies the CBF condition and…
Distributionally Robust Lyapunov Function Search Under Uncertainty
Kehan Long, Yinzhuang Yi, Jorge Cortes +1
This paper develops methods for proving Lyapunov stability of dynamical systems subject to disturbances with an unknown distribution. We assume only a finite set of disturbance sam…
Policy Learning for Active Target Tracking over Continuous SE(3) Trajectories
Pengzhi Yang, Shumon Koga, Arash Asgharivaskasi +1
This paper proposes a novel model-based policy gradient algorithm for tracking dynamic targets using a mobile robot, equipped with an onboard sensor with limited field of view. The…
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems
Valentin Duruisseaux, Thai Duong, Melvin Leok +1
Incorporating prior knowledge of physics laws and structural properties of dynamical systems into the design of deep learning architectures has proven to be a powerful technique fo…
Control Synthesis for Stability and Safety by Differential Complementarity Problem
Yinzhuang Yi, Shumon Koga, Bogdan Gavrea +1
This paper develops a novel control synthesis method for safe stabilization of control-affine systems as a Differential Complementarity Problem (DCP). Our design uses a control Lya…
Safe and Stable Control Synthesis for Uncertain System Models via Distributionally Robust Optimization
Kehan Long, Yinzhuang Yi, Jorge Cortes +1
This paper considers enforcing safety and stability of dynamical systems in the presence of model uncertainty. Safety and stability constraints may be specified using a control bar…
Information-theoretic Abstraction of Semantic Octree Models for Integrated Perception and Planning
Daniel T. Larsson, Arash Asgharivaskasi, Jaein Lim +2
In this paper, we develop an approach that enables autonomous robots to build and compress semantic environment representations from point-cloud data. Our approach builds a three-d…
Learning Continuous Control Policies for Information-Theoretic Active Perception
Pengzhi Yang, Yuhan Liu, Shumon Koga +2
This paper proposes a method for learning continuous control policies for active landmark localization and exploration using an information-theoretic cost. We consider a mobile rob…
LEMURS: Learning Distributed Multi-Robot Interactions
Eduardo Sebastian, Thai Duong, Nikolay Atanasov +2
This paper presents LEMURS, an algorithm for learning scalable multi-robot control policies from cooperative task demonstrations. We propose a port-Hamiltonian description of the m…
Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams
Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi +3
This paper considers the problem of safely coordinating a team of sensor-equipped robots to reduce uncertainty about a dynamical process, where the objective trades off information…
Robust and Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics
Zhichao Li, Thai Duong, Nikolay Atanasov
Stability and safety are critical properties for successful deployment of automatic control systems. As a motivating example, consider autonomous mobile robot navigation in a compl…
A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers
Julio A. Placed, Jared Strader, Henry Carrillo +4
Active Simultaneous Localization and Mapping (SLAM) is the problem of planning and controlling the motion of a robot to build the most accurate and complete model of the surroundin…
Latent Policies for Adversarial Imitation Learning
Tianyu Wang, Nikhil Karnwal, Nikolay Atanasov
This paper considers learning robot locomotion and manipulation tasks from expert demonstrations. Generative adversarial imitation learning (GAIL) trains a discriminator that disti…
Active Mapping via Gradient Ascent Optimization of Shannon Mutual Information over Continuous SE(3) Trajectories
Arash Asgharivaskasi, Shumon Koga, Nikolay Atanasov
The problem of active mapping aims to plan an informative sequence of sensing views given a limited budget such as distance traveled. This paper consider active occupancy grid mapp…
TerrainMesh: Metric-Semantic Terrain Reconstruction from Aerial Images Using Joint 2D-3D Learning
Qiaojun Feng, Nikolay Atanasov
This paper considers outdoor terrain mapping using RGB images obtained from an aerial vehicle. While feature-based localization and mapping techniques deliver real-time vehicle odo…
Safe Control Synthesis with Uncertain Dynamics and Constraints
Kehan Long, Vikas Dhiman, Melvin Leok +2
This paper considers safe control synthesis for dynamical systems with either probabilistic or worst-case uncertainty in both the dynamics model and the safety constraints. We form…
Physics-guided Learning-based Adaptive Control on the SE(3) Manifold
Thai Duong, Nikolay Atanasov
In real-world robotics applications, accurate models of robot dynamics are critical for safe and stable control in rapidly changing operational conditions. This motivates the use o…
Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics
Zhichao Li, Thai Duong, Nikolay Atanasov
Safe autonomous navigation in unknown environments is an important problem for mobile robots. This paper proposes techniques to learn the dynamics model of a mobile robot from traj…
Semantic OcTree Mapping and Shannon Mutual Information Computation for Robot Exploration
Arash Asgharivaskasi, Nikolay Atanasov
Autonomous robot operation in unstructured and unknown environments requires efficient techniques for mapping and exploration using streaming range and visual observations. Informa…
Active SLAM over Continuous Trajectory and Control: A Covariance-Feedback Approach
Shumon Koga, Arash Asgharivaskasi, Nikolay Atanasov
This paper proposes a novel active Simultaneous Localization and Mapping (SLAM) method with continuous trajectory optimization over a stochastic robot dynamics model. The problem i…
Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication
James Di, Ehsan Zobeidi, Alec Koppel +1
Multi-agent mapping is a fundamentally important capability for autonomous robot task coordination and execution in complex environments. While successful algorithms have been prop…