MOTION-PLANNINGCURRENT2026-05-04

Visibility-Aware Mobile Grasping in Dynamic Environments

Tianrun Hu, Anxing Xiao, David Hsu, Hanbo Zhang

This paper solves a key Manipulation & TasksMobile manipulationA robot both moves around and manipulates objects. problem: how to grab objects in unknown, dynamic environments when the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. can only see what's in front of it. The system balances Imitation & Reinforcement LearningExplorationTrying different actions to discover useful behavior. (turning to see around) with Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. progress (moving to grasp), achieving 58% success in dynamic scenarios—a 18% improvement over prior work while keeping the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. collision-safe.

ARCHITECTURE

THE PROBLEM

This paper focuses on Control & PlanningMotion planningFinding a path or motion that gets the robot from start to goal.. This paper solves a key Manipulation & TasksMobile manipulationA robot both moves around and manipulates objects. problem: how to grab objects in unknown, dynamic environments when the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. can only see what's in front of it. The system balances Imitation & Reinforcement LearningExplorationTrying different actions to discover useful behavior. (turning to see around) with Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. progress (moving to grasp), achieving 58% success in dynamic scenarios—a 18% improvement over prior work while keeping the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. collision-safe. Read the paper by tracking the Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. definition, the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. or data assumptions, and the evidence that supports the claimed improvement.

HOW IT WORKS

1

Task framing

The paper frames the work as Control & PlanningMotion planningFinding a path or motion that gets the robot from start to goal.. Start here because it defines what success means and which assumptions the rest of the method inherits.

2

Core method

This paper solves a key Manipulation & TasksMobile manipulationA robot both moves around and manipulates objects. problem: how to grab objects in unknown, dynamic environments when the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. can only see what's in front of it. The system balances Imitation & Reinforcement LearningExplorationTrying different actions to discover useful behavior. (turning to see around) with Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. progress (moving to grasp), achieving 58% success in dynamic scenarios—a 18% improvement over prior work while keeping the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. collision-safe. When reading the method section, identify the inputs, the learned or engineered representation, and the Core ConceptsActionA command the robot sends to its motors, controller, or low-level system. or prediction produced by the system.

3

Data and supervision

For robotics work, the data story is part of the method: check whether the system depends on Imitation & Reinforcement LearningTeleoperation (teleop)A human remotely controlling the robot, often to collect demonstrations., Simulation & Sim-to-RealSimulationA virtual environment where robots can be trained or tested., internet video, human labels, or Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. rollouts.

4

Evaluation evidence

The paper should be judged through its Simulation & Sim-to-RealEvaluationMeasuring how well a robot system performs. protocol: what data is used, what Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. or simulator is tested, and which Evaluation & ResearchBaselineA reference method used for comparison. comparisons support the claim. Look for the gap between the headline result and the Simulation & Sim-to-RealDeploymentPutting the trained system on a real robot. setting you would actually care about.

FIGURES

KEY RESULTS

Main contributionConceptual contribution

This paper solves a key Manipulation & TasksMobile manipulationA robot both moves around and manipulates objects. problem: how to grab objects in unknown, dynamic environments when the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. can only see what's in front of it. The system balances Imitation & Reinforcement LearningExplorationTrying different actions to discover useful behavior. (turning to see around) with Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. progress (moving to grasp), achieving 58% success in dynamic scenarios—a 18% improvement over prior work while keeping the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. collision-safe.

WHY DEVELOPERS SHOULD CARE

This paper solves a key Manipulation & TasksMobile manipulationA robot both moves around and manipulates objects. problem: how to grab objects in unknown, dynamic environments when the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. can only see what's in front of it. The system balances Imitation & Reinforcement LearningExplorationTrying different actions to discover useful behavior. (turning to see around) with Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. progress (moving to grasp), achieving 58% success in dynamic scenarios—a 18% improvement over prior work while keeping the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. collision-safe.

LIMITATIONS

The main limitation to check is whether the claimed behavior holds outside the paper's reported setup. That means testing across different Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. embodiments, scenes, objects, and data distributions.

WHAT COMES NEXT

The practical next step is independent reproduction with clear baselines, ablations, and stress tests. For a developer, the useful follow-up is to map the paper's Control & PlanningMotion planningFinding a path or motion that gets the robot from start to goal. assumptions onto a concrete Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. stack, then test the smallest version of the method that could run end to end.

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