Goal-Directed Local Navigation
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Related Articles from SNS
3D RL-DWA: A Hybrid Reinforcement Learning and Dynamic Window Approach for Goal-Directed Local Navigation in Multi-DoF Robots
Announce Type: replace Abstract: In this paper, we present a novel hybrid approach that combines Reinforcement Learning (RL) with Dynamic Window Approach (DWA) for adaptive 3D local navigation of high-degree-of-freedom robotic systems. Our method leverages sparse point cloud data to dynamically adjust both the motion and the shape of a deformable microrobot, enabling the system to navigate toward a goal in complex, constrained environments while maximizing the occupied volume. We evaluate...
Distance Mapping and Variable-Specific Geometry of Goal-Relevant Frames in the Retrosplenial Cortex
Goal-directed navigation requires animals to continuously update their position relative to an unmarked goal. Here, we recorded retrosplenial cortex (RSC) activity in freely moving rats during goal-directed navigation and random foraging. We found that RSC neurons encoded the Euclidean distance to the goal, and that this distance representation was selectively biased toward the goal during navigation.
Learning-Based Navigation for Indoor Mobile Robots
arXiv:2605.30468v1 Announce Type: new Abstract: This paper presents a learning-based navigation framework for indoor mobile robots. The proposed method combines a supervised neural global planner, trained from cost-aware A* expert trajectories, with the proposed Learning-Based DWA local planner, which is formulated as discrete candidate selection over the Dynamic Window Approach (DWA) action lattice. For local planning, the policy is first trained by behavior cloning and then refined by...
TARIC: Memory-Augmented Traversability-Aware Outdoor VLN under Interrupted Semantic Cues
arXiv:2605.31121v1 Announce Type: new Abstract: Outdoor vision-language navigation (VLN) in long-range, open-world environments is frequently disrupted by semantic-cue interruptions, where informative goal cues become sparse, occluded, or leave the field of view. Once such cues disappear, agents enter a cue-free phase and often degrade into backtracking, oscillatory headings, or aimless exploration. While memory-based methods attempt to bridge these gaps, they often fail under...