TinySDP is the first semidefinite programming solver designed for embedded systems, enabling real-time certifiable model predictive control with nonconvex geometric constraints on microcontrollers.
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In: 2022 International Conference on Robotics and Automation (ICRA), pp
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representative citing papers
Optimal configurations for regular-chassis fully-actuated multirotors reduce to N-5 disconnected 1D topological branches corresponding to star polygons {N/q}.
Promptbreeder evolves both task prompts and the mutation prompts that improve them using LLMs, outperforming Chain-of-Thought and Plan-and-Solve on arithmetic and commonsense reasoning benchmarks.
Introduces and evaluates an intent-first aerial V2V protocol using C-V2X sidelink for tactical coordination and separation in dense UTM operations, showing viability in moderate regimes with fallback at high density.
A Galilean-equivariant filter jointly estimates INS navigation states and unknown GNSS time delays, preserving accuracy and consistency better than EKF in UAV flights and simulations with delays up to 500 ms.
LLM-Foraging uses off-the-shelf LLMs for decentralized tactical decisions in CPFA-based swarm foraging, collecting more resources than GA-tuned baselines across 36 varied configurations while showing greater consistency.
SARR modifies trigonometric rotation encodings with object symmetry orders to produce unique continuous poses, enabling standard CNNs to outperform existing methods on symmetry-aware 6D pose estimation without custom losses or 3D models.
A conditional diffusion model using proprioception and multi-contact touch produces metric-scale, physically consistent 3D object reconstructions under hand occlusion.
The virtual object MPC framework enables stable shared teleoperation for transporting up to nine objects, cutting sliding distance by 72.45% and eliminating tip-overs compared to baseline.
Free-Range Gaussians uses flow matching over Gaussian parameters to predict non-grid-aligned 3D Gaussians from multi-view images, enabling synthesis of plausible content in unobserved regions with fewer primitives than grid-aligned methods.
Task-level ILC learns flying knot rope manipulation from one demo, achieving 100% success within 10 trials on 7 rope types with 2-5 trial transfers.
AID trains diffusion policies via behavior cloning on existing MAIPP planners followed by RL fine-tuning to achieve faster execution and higher information gain in multi-agent coordination.
Guided RL using Bezier curves and UARM model enables efficient, explainable omnidirectional jumping in quadruped robots.
Hyper-V2X uses a Bayesian hypernetwork with partial weight generation and V2X context embedding to produce calibrated epistemic and aleatoric uncertainty estimates for multi-agent BEV segmentation on the OPV2V benchmark.
UniTrans pretrains a bank of translator experts and learns combination coefficients from modality mappings in a scene-invariant latent space to enable zero-shot any-to-any feature translation for heterogeneous collaborative perception.
Recasts sampling-based nonconvex optimization as smoothed gradient descent to obtain non-asymptotic convergence guarantees and introduces the DIDA annealed algorithm that converges to the global optimum.
T3S is a new semantic similarity score for processed images that decomposes semantics into foreground entities, background entities, and relations, outperforming fidelity metrics on COCO and SPA-Data.
frax is a new open-source JAX library delivering low-microsecond CPU dynamics and over 100 million GPU evaluations per second for robot kinematics and dynamics with autodiff support.
A 2084-parameter recurrent policy trained by distilling 1000 RL teacher policies enables zero-shot control across 10 real quadrotors differing in mass, motors, frames, propellers, and flight controllers.
MVDream is a multi-view diffusion model that functions as a generalizable 3D prior, enabling more consistent text-to-3D generation and few-shot 3D concept learning from 2D examples.
A simulation-trained deep deformation model combined with online adaptive control enables zero-shot autonomous tissue retraction for ROI exposure in robotic surgery.
Systematic grasping strategies for paper-like materials are developed and tested with a soft gripper by exploiting environmental constraints to improve force control and success rates.
Planetary Exploration 3.0 proposes single adaptive missions that perform both initial exploration and follow-on science on unvisited worlds using software-defined space systems.
GMP selectively activates and represents memory via a gate and lightweight cross-attention, yielding 30.1% higher success on non-Markovian robotic tasks while staying competitive on Markovian ones.
citing papers explorer
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TinySDP: Real Time Semidefinite Optimization for Certifiable and Agile Edge Robotics
TinySDP is the first semidefinite programming solver designed for embedded systems, enabling real-time certifiable model predictive control with nonconvex geometric constraints on microcontrollers.
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The N-5 Scaling Law: Topological Dimensionality Reduction in the Optimal Design of Fully-actuated Multirotors
Optimal configurations for regular-chassis fully-actuated multirotors reduce to N-5 disconnected 1D topological branches corresponding to star polygons {N/q}.
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Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution
Promptbreeder evolves both task prompts and the mutation prompts that improve them using LLMs, outperforming Chain-of-Thought and Plan-and-Solve on arithmetic and commonsense reasoning benchmarks.
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Intent-First Aerial V2V for Tactical Coordination and Separation: Protocol and Performance Under Density and Disturbance
Introduces and evaluates an intent-first aerial V2V protocol using C-V2X sidelink for tactical coordination and separation in dense UTM operations, showing viability in moderate regimes with fallback at high density.
-
Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay
A Galilean-equivariant filter jointly estimates INS navigation states and unknown GNSS time delays, preserving accuracy and consistency better than EKF in UAV flights and simulations with delays up to 500 ms.
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LLM-Foraging: Large Language Models for Decentralized Swarm Robot Foraging
LLM-Foraging uses off-the-shelf LLMs for decentralized tactical decisions in CPFA-based swarm foraging, collecting more resources than GA-tuned baselines across 36 varied configurations while showing greater consistency.
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Towards Symmetry-sensitive Pose Estimation: A Rotation Representation for Symmetric Object Classes
SARR modifies trigonometric rotation encodings with object symmetry orders to produce unique continuous poses, enabling standard CNNs to outperform existing methods on symmetry-aware 6D pose estimation without custom losses or 3D models.
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Physically Grounded 3D Generative Reconstruction under Hand Occlusion using Proprioception and Multi-Contact Touch
A conditional diffusion model using proprioception and multi-contact touch produces metric-scale, physically consistent 3D object reconstructions under hand occlusion.
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Towards Multi-Object Nonprehensile Transportation via Shared Teleoperation: A Framework Based on Virtual Object Model Predictive Control
The virtual object MPC framework enables stable shared teleoperation for transporting up to nine objects, cutting sliding distance by 72.45% and eliminating tip-overs compared to baseline.
-
Free-Range Gaussians: Non-Grid-Aligned Generative 3D Gaussian Reconstruction
Free-Range Gaussians uses flow matching over Gaussian parameters to predict non-grid-aligned 3D Gaussians from multi-view images, enabling synthesis of plausible content in unobserved regions with fewer primitives than grid-aligned methods.
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Learning Dynamic Rope Manipulation Using Task-Level Iterative Learning Control
Task-level ILC learns flying knot rope manipulation from one demo, achieving 100% success within 10 trials on 7 rope types with 2-5 trial transfers.
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AID: Agent Intent from Diffusion for Multi-Agent Informative Path Planning
AID trains diffusion policies via behavior cloning on existing MAIPP planners followed by RL fine-tuning to achieve faster execution and higher information gain in multi-agent coordination.
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Guided Reinforcement Learning for Omnidirectional 3D Jumping in Quadruped Robots
Guided RL using Bezier curves and UARM model enables efficient, explainable omnidirectional jumping in quadruped robots.
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Hyper-V2X: Hypernetworks for Estimating Epistemic and Aleatoric Uncertainty in Cooperative Bird's-Eye-View Semantic Segmentation
Hyper-V2X uses a Bayesian hypernetwork with partial weight generation and V2X context embedding to produce calibrated epistemic and aleatoric uncertainty estimates for multi-agent BEV segmentation on the OPV2V benchmark.
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One Model to Translate Them All: Universal Any-to-Any Translation for Heterogeneous Collaborative Perception
UniTrans pretrains a bank of translator experts and learns combination coefficients from modality mappings in a scene-invariant latent space to enable zero-shot any-to-any feature translation for heterogeneous collaborative perception.
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Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing
Recasts sampling-based nonconvex optimization as smoothed gradient descent to obtain non-asymptotic convergence guarantees and introduces the DIDA annealed algorithm that converges to the global optimum.
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Beyond Fidelity: Semantic Similarity Assessment in Low-Level Image Processing
T3S is a new semantic similarity score for processed images that decomposes semantics into foreground entities, background entities, and relations, outperforming fidelity metrics on COCO and SPA-Data.
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frax: Fast Robot Kinematics and Dynamics in JAX
frax is a new open-source JAX library delivering low-microsecond CPU dynamics and over 100 million GPU evaluations per second for robot kinematics and dynamics with autodiff support.
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RAPTOR: A Foundation Policy for Quadrotor Control
A 2084-parameter recurrent policy trained by distilling 1000 RL teacher policies enables zero-shot control across 10 real quadrotors differing in mass, motors, frames, propellers, and flight controllers.
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MVDream: Multi-view Diffusion for 3D Generation
MVDream is a multi-view diffusion model that functions as a generalizable 3D prior, enabling more consistent text-to-3D generation and few-shot 3D concept learning from 2D examples.
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Learning-Based Adaptive Control for Surgical Robotic Exposure Task on Deformable Tissues
A simulation-trained deep deformation model combined with online adaptive control enables zero-shot autonomous tissue retraction for ROI exposure in robotic surgery.
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Introducing Environmental Constraints to Grasping Strategies for Paper-Like Flexible Materials Using a Soft Gripper
Systematic grasping strategies for paper-like materials are developed and tested with a soft gripper by exploiting environmental constraints to improve force control and success rates.
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Planetary Exploration 3.0: A Roadmap for Software-Defined, Radically Adaptive Space Systems
Planetary Exploration 3.0 proposes single adaptive missions that perform both initial exploration and follow-on science on unvisited worlds using software-defined space systems.
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Gated Memory Policy
GMP selectively activates and represents memory via a gate and lightweight cross-attention, yielding 30.1% higher success on non-Markovian robotic tasks while staying competitive on Markovian ones.
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Robotic Nanoparticle Synthesis via Solution-based Processes
Screw-based motion planning extracted from single demonstrations enables robots to autonomously execute long-horizon nanoparticle synthesis protocols.
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BEVPredFormer: Spatio-temporal Attention for BEV Instance Prediction in Autonomous Driving
BEVPredFormer uses attention-based temporal processing and 3D camera projection to match or exceed prior methods on nuScenes for BEV instance prediction.
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STL-Based Motion Planning and Uncertainty-Aware Risk Analysis for Human-Robot Collaboration with a Multi-Rotor Aerial Vehicle
The paper proposes an STL-based optimization planner with uncertainty-aware risk analysis and event-triggered replanning for safe human-drone collaboration, demonstrated in simulations of an object handover task.
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Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardware
RSR-RSMARL is a robust safe MARL framework with V2V communication and CBF safety shields that supports zero-shot sim-to-real transfer and improves coordination on 1/10-scale vehicle hardware.
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Behavior Synthesis via Contact-Aware Fisher Information Maximization
Derives a contact-aware Fisher information measure to synthesize robot behaviors that maximize information-rich contacts for efficient object parameter learning.
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Out-of-Distribution Generalization in Time Series: A Survey
This is the first comprehensive survey of OOD generalization methodologies for time series, organized across data distribution, representation learning, and OOD evaluation.
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The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy
An open-sourced Unified Autonomy Stack fuses LiDAR, radar, vision and inertial data with sampling-based planning and control barrier functions to deliver resilient autonomy on aerial and ground robots in challenging real-world settings.
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Smoothing Out the Edges: Continuous-Time Estimation with Gaussian Process Motion Priors on Factor Graphs
The paper recasts Gaussian-process continuous-time estimation in factor-graph language and supplies three GTSAM implementations to lower the barrier to adoption.
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DigiForest: Digital Analytics and Robotics for Sustainable Forestry
DigiForest integrates heterogeneous autonomous robots for data collection, automated tree trait extraction, a decision support system for growth forecasting, and autonomous harvesters for selective logging, with real-world tests in European forests.
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Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions
A survey of trajectory prediction techniques for autonomous vehicles that proposes a taxonomy, overviews the prediction pipeline, and highlights remaining research gaps.
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Comprehensive Review of Doppler Shift Localization Methods: Advances, Limitations, and Research Opportunities
A survey that unifies over a decade of Doppler-based localization research into five technique families, compares inference methods under impairments, and identifies open challenges for practical deployments.