ICRA 2026 Past RoboticsReinforcement learning
IEEE ICRA 2026 Workshop on Cross-Disciplinary aspects of Exploration in Robotics, Reinforcement Learning and Search (Xplore)
IEEE ICRA 2026 Workshop Xplore
- Submission deadline
-
TBA — know
the deadline? Add it in one line The file opens with a ready-to-fill template — takes about a minute.
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (26)
Fetched from OpenReview (v2) on 2026-06-10.
-
Bayesian Optimization for Learning Nonlinear MPC in Autonomous Agent Navigation
-
BEACON: Belief-Aware Replanning for Safe Online Motion Planning
-
Beyond Reactive Adaptation: Long-Horizon Memory for Autonomous Racing via State Space Models
-
CACTO-BIC: Scalable Actor-Critic Learning via Biased Sampling and GPU-Accelerated Trajectory Optimization
-
Coupling-Aware Planner Exploration for Shared-Workspace Multi-Manipulator Motion Planning
-
CRAFT: Coaching Reinforcement Learning Autonomously using Foundation Models for Multi-Robot Coordination Tasks
-
Efficient Rare-Event Sampling in Diffusion Policies for Motion Discovery
-
Exploration-Exploitation Prompting: A Dual-Process Framework for Complex Mathematical Problem Solving
-
Feasibility-Constrained Diffusion-MPC for Discrete Combinatorial Planning: A Case Study on Tetris
-
From Exploration to Reuse: An Embodied Agent Framework for Manipulation Skill Learning
-
From Simulation to Contact: A Modular Wrench-Space Deployment Stack for Multi-Task Robot Manipulation
-
GPS-Denied Rover Motion Regulation as a Physically Grounded POMDP for Recurrent Reinforcement Learning
-
Graph-Structured Reinforcement Learning for Controlling a Transformable-Wheel Robot
-
IFG: Internet-Scale Guidance for Functional Grasping Generation
-
Learning Temporally and State-Abstracted World Models for Long-Horizon Exploration
-
LLM-Guided Future Hypotheses for Horizon-Aware Exploration in Multi-Step Robot Manipulation
-
MineXplore: An Open-Source Reinforcement Learning Exploration Benchmark for GNSS-Denied Underground Environment
-
Mixture of Autoencoder Experts Guidance using Unlabeled and Incomplete Data for Exploration in Reinforcement Learning
-
Mobile robots exploration strategies and requirements: A systematic mapping study
-
Multi-Robot Frontier-Based Exploration under Uncertainty with SLAM and Temporal Map Fusion
-
Representation-Driven Exploration for Long-Horizon Manipulation
-
Stability-Guided Exploration for Diverse Motion Generation
-
Towards Semantic-Aware Active Gas Distribution Mapping in Unknown Cluttered Environments
-
Truncated Gaussian Policy for Debiased Exploration in Continuous Control
-
Variable-Resolution Virtual Map Guided Informed Tree Search for Autonomous USV Exploration
-
Variable-Resolution Virtual Maps for Autonomous Exploration with Unmanned Surface Vehicles (USVs)