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09/19/2023
Asymptotically Optimal Belief Space Planning in Discrete Partially-Observable Domains
Robots often have to operate in discrete partially observable worlds, wh...
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09/14/2023
Neural Field Representations of Articulated Objects for Robotic Manipulation Planning
Traditional approaches for manipulation planning rely on an explicit geo...
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06/29/2023
Spatial Reasoning via Deep Vision Models for Robotic Sequential Manipulation
In this paper, we propose using deep neural architectures (i.e., vision ...
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05/27/2023
Towards computing low-makespan solutions for multi-arm multi-task planning problems
We propose an approach to find low-makespan solutions to multi-robot mul...
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04/27/2023
Comparison of Optimization-Based Methods for Energy-Optimal Quadrotor Motion Planning
Quadrotors are agile flying robots that are challenging to control. Cons...
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03/06/2023
PaLM-E: An Embodied Multimodal Language Model
Large language models excel at a wide range of complex tasks. However, e...
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03/01/2023
Efficient Path Planning In Manipulation Planning Problems by Actively Reusing Validation Effort
The path planning problems arising in manipulation planning and in task ...
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01/31/2023
Control-Tree Optimization: an approach to MPC under discrete Partial Observability
This paper presents a new approach to Model Predictive Control for envir...
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12/06/2022
Solving Rearrangement Puzzles using Path Defragmentation in Factored State Spaces
Rearrangement puzzles are variations of rearrangement problems in which ...
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11/28/2022
A Conflict-driven Interface between Symbolic Planning and Nonlinear Constraint Solving
Robotic planning in real-world scenarios typically requires joint optimi...
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10/24/2022
Planning Coordinated Human-Robot Motions with Neural Network Full-Body Prediction Models
Numerical optimization has become a popular approach to plan smooth moti...
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10/22/2022
Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning
A factored Nonlinear Program (Factored-NLP) explicitly models the depend...
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06/03/2022
Reinforcement Learning with Neural Radiance Fields
It is a long-standing problem to find effective representations for trai...
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05/17/2022
Effort Informed Roadmaps (EIRM*): Efficient Asymptotically Optimal Multiquery Planning by Actively Reusing Validation Effort
Multiquery planning algorithms find paths between various different star...
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05/09/2022
FC^3: Feasibility-Based Control Chain Coordination
Hierarchical coordination of controllers often uses symbolic state repre...
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04/09/2022
Path-Tree Optimization in Partially Observable Environments using Rapidly-Exploring Belief-Space Graphs
Robots often need to solve path planning problems where essential and di...
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03/21/2022
db-A*: Discontinuity-bounded Search for Kinodynamic Mobile Robot Motion Planning
We consider time-optimal motion planning for dynamical systems that are ...
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03/10/2022
Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation
Task and Motion Planning has made great progress in solving hard sequent...
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03/04/2022
ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time
We present a motion planner for planning through space-time with dynamic...
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03/03/2022
BITKOMO: Combining Sampling and Optimization for Fast Convergence in Optimal Motion Planning
Optimal sampling based motion planning and trajectory optimization are t...
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02/24/2022
Learning Multi-Object Dynamics with Compositional Neural Radiance Fields
We present a method to learn compositional predictive models from image ...
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12/13/2021
MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets
Recently, there has been a wealth of development in motion planning for ...
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12/09/2021
Learning Neural Implicit Functions as Object Representations for Robotic Manipulation
Robotic manipulation planning is the problem of finding a sequence of ro...
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11/15/2021
Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics
Applications of Reinforcement Learning (RL) in robotics are often limite...
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10/28/2021
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Machine learning has long since become a keystone technology, accelerati...
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10/07/2021
RHH-LGP: Receding Horizon And Heuristics-Based Logic-Geometric Programming For Task And Motion Planning
Sequential decision-making and motion planning for robotic manipulation ...
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10/02/2021
Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning
This work proposes an optimization-based manipulation planning framework...
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08/24/2021
Learning to Arbitrate Human and Robot Control using Disagreement between Sub-Policies
In the context of teleoperation, arbitration refers to deciding how to b...
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07/30/2021
Active Learning in Gaussian Process State Space Model
We investigate active learning in Gaussian Process state-space models (G...
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07/14/2021
Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks
In high-dimensional state spaces, the usefulness of Reinforcement Learni...
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07/06/2021
Approximate Topological Optimization using Multi-Mode Estimation for Robot Motion Planning
In this extended abstract, we report on ongoing work towards an approxim...
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07/05/2021
GraspME – Grasp Manifold Estimator
In this paper, we introduce a Grasp Manifold Estimator (GraspME) to dete...
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07/05/2021
A System for Traded Control Teleoperation of Manipulation Tasks using Intent Prediction from Hand Gestures
This paper presents a teleoperation system that includes robot perceptio...
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06/04/2021
Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly
Robotic assembly planning has the potential to profoundly change how bui...
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04/16/2021
Hierarchical Human-Motion Prediction and Logic-Geometric Programming for Minimal Interference Human-Robot Tasks
In this paper, we tackle the problem of human-robot coordination in sequ...
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03/09/2021
Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping
Robotic manipulation of unknown objects is an important field of researc...
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01/28/2021
Visualization of Nonlinear Programming for Robot Motion Planning
Nonlinear programming targets nonlinear optimization with constraints, w...
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11/23/2020
MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze
As robots become more present in open human environments, it will become...
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11/09/2020
Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation
Efficient sampling from constraint manifolds, and thereby generating a d...
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11/03/2020
Efficient Sampling of Transition Constraints for Motion Planning under Sliding Contacts
Contact-based motion planning for manipulation, object exploration or ba...
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11/02/2020
Sparse Multilevel Roadmaps on Fiber Bundles for High-Dimensional Motion Planning
Sparse roadmaps are important to compactly represent state spaces, to de...
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10/27/2020
Section Patterns: Efficiently Solving Narrow Passage Problems using Multilevel Motion Planning
Sampling-based planning methods often become inefficient due to narrow p...
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07/30/2020
Natural Gradient Shared Control
We propose a formalism for shared control, which is the problem of defin...
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07/20/2020
Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks
Motion prediction in unstructured environments is a difficult problem an...
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07/18/2020
Multilevel Motion Planning: A Fiber Bundle Formulation
Motion planning problems involving high-dimensional state spaces can oft...
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07/15/2020
Qgraph-bounded Q-learning: Stabilizing Model-Free Off-Policy Deep Reinforcement Learning
In state of the art model-free off-policy deep reinforcement learning, a...
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07/09/2020
An Interior Point Method Solving Motion Planning Problems with Narrow Passages
Algorithmic solutions for the motion planning problem have been investig...
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06/09/2020
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image
In this paper, we propose a deep convolutional recurrent neural network ...
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03/29/2020
Optimized Directed Roadmap Graph for Multi-Agent Path Finding Using Stochastic Gradient Descent
We present a novel approach called Optimized Directed Roadmap Graph (ODR...
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03/17/2020