Reactive local planners such as the Dynamic Window Approach (DWA) often fail in non-convex dead-end structures because their greedy objective drives the robot into local minima. This paper presents a ROS 2-native mapless navigation framework that trains a Proximal Policy Optimization (PPO) agent using a Procedural Adversarial Trap Generator (ATG) in Gazebo. The generator systematically produces U-shaped traps, corners, and narrow passages so that the agent learns proactive avoidance and recovery behavior rather than merely reacting to nearby obstacles. In simulation, the proposed DRL policy achieves an 88% success rate in complex maze scenarios, while the DWA baseline drops to 8%. A zero-shot deployment on a physical Unitree Go2 further confirms that the learned behavior transfers to real hardware despite LiDAR noise and odometry uncertainty.
Ardiansyah Al Farouq, Yuya Hosoda, Jooho Lee· 2026 23rd International Conf...· 0 citations
Wearable electromyography (EMG) interfaces enable natural human-robot interaction, and low-density configurations are preferred for practical deployment due to their simplicity and cost-effectiveness. However, limited spatial information challenges reliable and timely pattern recognition. This study compares three segmentation strategies for three-channel EMG gesture recognition - fixed sliding window, event-gated adaptive thresholding, and Teager-Kaiser energy operator (TKEO) - evaluated on six gestures from eight subjects under leave-one-subject-out cross-validation with BiLSTM+Attention classification. Mean classification accuracies ranged from 59.17% (fixed window) to 64.39% (adaptive), with no statistically significant differences among methods (p > 0.18). Temporal evaluation showed mean onset-to-decision latencies of 113.9 ms (TKEO), 137.7 ms (fixed window), and 149.7 ms (adaptive) - all within the 300 ms real-time feasibility threshold. Cross-subject variability (26-88%) substantially exceeded inter-method differences, suggesting that subject-specific factors are a more critical performance determinant than segmentation strategy. These results are intended as a direction-confirming study for temporal processing design in low-channel wearable EMG systems; statistical generalization to larger populations is reserved for future work.
