Agile
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Related Articles from SNS
Overcoming Challenges in Agile and DevOps Integration: A Qualitative Study
arXiv:2606.01676v1 Announce Type: new Abstract: In response to the growing reliance on Agile and DevOps methodologies for enhancing software delivery speed and quality, this study investigates the persistent challenges and viable solutions associated with their integration. Although Agile promotes iterative development and customer responsiveness, and DevOps emphasizes automation and operational efficiency, their convergence in practice often presents significant organizational, structural,...
Neurodiversity in Agile Teams: Obstacles and Inclusion Barriers
Announce Type: new Abstract: Context: Neurodiversity is increasingly recognized as a valuable dimension of workplace diversity. However, in agile software development teams, the interplay between teamwork practices and the inclusion of neurodivergent employees remains underexplored.
VAIC: Vision-Guided Humanoid Agile Object Interaction Control via Decoupled Commands
arXiv:2606.09286v1 Announce Type: new Abstract: Humanoid robots hold immense potential for real-world assistance, yet agile interaction with objects in unstructured environments demands tightly coupled whole-body coordination. Despite recent advancements, current controllers face a critical deployment gap. They rely heavily on dense reference trajectories and perfect state observability, which inherently limits physical generalization.
TAGA: Terrain-aware Active Gaze Learning for Generalizable Agile Humanoid Locomotion
arXiv:2606.05880v1 Announce Type: new Abstract: Agile humanoid locomotion across diverse challenging terrain demands both wide perceptual coverage and precise local geometry understanding. Motivated by the way humans selectively look at relevant terrain during locomotion, we introduce TAGA, a Terrain-aware Active Gaze learning framework for Attention-based humanoid control. By fusing vision, proprioception, and motion commands, our framework guides the model to learn anticipatory cues and...
TRANS: Terrain-aware Reinforcement Learning for Agile Navigation of Quadruped Robots under Social Interactions
arXiv:2602.12724v3 Announce Type: replace Abstract: This study introduces TRANS: Terrain-aware Reinforcement learning for Agile Navigation under Social interactions, a deep reinforcement learning (DRL) framework for quadrupedal social navigation over unstructured terrains. Conventional quadrupedal navigation typically separates motion planning from locomotion control, neglecting whole-body constraints and terrain awareness. On the other hand, end-to-end methods are more integrated but...
PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion
arXiv:2606.03441v1 Announce Type: new Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to the limited field of view (FOV). In this paper, we propose PerchRL, a reinforcement learning (RL) framework for vision-based agile perching on inclined platforms under rapid and irregular motion. Specifically, we employ a two-stage learning strategy consisting of state-based pre-training followed by...
MAD: Mapping-Aware World Models for Agile Quadrotor Flight
Announce Type: new Abstract: Agile quadrotor flight in cluttered scenes requires more than a reactive mapping from a depth image to a control command: the vehicle must remember which regions have been observed, infer nearby occupied space, and act under partial visibility and tight latency. In this paper, we present Mapping-Aware Dreamer (MAD), a geometry-aware world model for vision-based quadrotor flight. Instead of using raw-image reconstruction as the main self-supervised objective, MAD...
Agile Online Model Selection: Resolving Adaptation Lag via Safeguarded Large Learning Rates
arXiv:2605.26919v2 Announce Type: replace Abstract: Maintaining predictive accuracy in non-stationary environments requires online model selection to adapt autonomously to unknown distribution shifts. However, existing tuning-free algorithms face a fundamental trade-off between robustness and agility. Specifically, to ensure dynamic regret bounds, they must restrict learning rates to small constants (e.g., $O(1)$).
A Preliminary Model for Managing Technical Debt in an Agile Environment
arXiv:2606.07859v1 Announce Type: new Abstract: This paper presents a preliminary model for managing involuntary technical debt in agile environments by formulating, in an integrated way, the dynamics among backlog, debt, velocity, and economic value. The work distinguishes initiated but unfinished functional debt from a simple defect back log and from rework, interprets productivity degradation as technical-debt interest, and derives the naive maximum-remediation policy in order to show its...
PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion
arXiv:2606.03441v2 Announce Type: replace Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to the limited field of view (FOV). In this paper, we propose PerchRL, a reinforcement learning (RL) framework for vision-based agile perching on inclined platforms under rapid and irregular motion. Specifically, we employ a two-stage learning strategy consisting of state-based pre-training...