The paper introduces Planning Diffusion Policy Optimization (PDPO), an offline‑to‑online reinforcement‑learning framework that employs a diffusion policy to produce short‑horizon action chunks for robot crowd navigation. PDPO is pretrained on collision‑avoidance demonstrations and fine‑tuned online with PPO, generating five‑step action sequences applied in a receding‑horizon manner. The authors also identify a benchmark artifact where agents can leave the valid domain without explicit boundary constraints, and they mitigate this by treating boundary violations as collisions, leading to improved success rates over strong baselines.
By Wendong Li, Jochen Garcke
arXiv:2606. 14763v1 Announce Type: cross Abstract: Real-time autonomous navigation in dynamic, unknown environments remains a fundamental challenge for mobile robotics.
By Lorenzo Ortolani, Gabriel Voss, Gabriele Beltrami, Francesco Dorati, Tommaso Felice Banfi
arXiv:2609.13083v2 Announce Type: replace-cross
Abstract: In urban search and rescue, articulated tracked robots (ATRs) must traverse structured but contact-rich environments such as stairwells and c...
By Zhenfeng Gan, Yanbo Chen, Lirong Che, Junbo Tan, Xueqian Wang
The paper introduces ASTRIL-MPC, a language‑guided neural model predictive control framework that enables articulated tracked robots to navigate complex, contact‑rich urban environments such as stairwells and cluttered interiors. By combining a learned kinematics model that predicts short‑horizon state changes, an optimization‑based planner with multi‑objective costs, and a large language model that safely updates control weights, the system achieves up to 71% better traversal quality than non‑adaptive NMPC and 67% better than a PPO baseline, while eliminating collision impacts during descent. Real‑robot trials over four indoor obstacles confirm the method’s transferability to physical contact‑rich traversal.
By Zhenfeng Gan, Yanbo Chen, Lirong Che, Yongyi Ma, Rongkai Zhu, Xueqian Wang
arXiv:2608. 09166v1 Announce Type: cross Abstract: Reliable uncertainty representation is essential for deploying autonomous systems that interact with their environment, as robots must reason about how uncertainty arising from both stochasticity and model mismatch is impacted by contacts with obstacles (e.
By Lu\'is Marques, Kristian Popov, Dmitry Berenson
arXiv:2604.15221v3 Announce Type: replace-cross
Abstract: Safe human-robot collaboration (HRC) requires accurate human pose estimation and motion prediction to prevent critical collisions. Existing c...
By Jakob Thumm, Marian Frei, Tianle Ni, Matthias Althoff, Marco Pavone
arXiv:2608. 10056v1 Announce Type: cross Abstract: Following a target human in crowded environments involves an inherent conflict between staying close to the target and navigating safely among surrounding pedestrians and obstacles.
By Shiting Gong, Jianpeng Yao, Jinfeng Wang, Marco Pavone, Jiachen Li
arXiv:2608.21175v1 Announce Type: cross
Abstract: Safe and efficient shape-aware navigation in heterogeneous crowds and robot fleets remains challenging. Traditional approaches often assume homogeneo...
By Ruihua Han, Rui Gao, Zhe Liu, Xinyi Wang, Chang Chen, Shuai Wang, Qi Hao, Jia Pan, Hengshuang Zhao
arXiv:2607. 17574v1 Announce Type: cross Abstract: Reinforcement-learning navigation policies for legged robots select actions reactively from current observations and short-term memory, with limited capacity to anticipate how moving obstacles will evolve in the near future.
By Yancheng Zhu, Wanli Ma, Chen Han, Irvin Haozhe Zhan, Bingfeng Qin, Yixin Xu
arXiv:2609.23731v1 Announce Type: cross
Abstract: Robotic systems are typically composed of multiple independently developed modules that work together to perceive, predict, and act in the environmen...
By Rista Baral
arXiv:2603. 08862v2 Announce Type: replace-cross Abstract: Autonomous navigation in highly constrained environments remains challenging for mobile robots.
By Yuanjie Lu, Beichen Wang, Zhengqi Wu, Yang Li, Xiaomin Lin, Chengzhi Mao, Xuesu Xiao
arXiv:2510.23576v2 Announce Type: replace-cross
Abstract: Urban micromobility applications, such as delivery robots, demand reliable navigation across large-scale urban environments while following l...
By Anqi Li, Zhiyong Wang, Jiazhao Zhang, Minghan Li, Yunpeng Qi, Zhibo Chen, Zhizheng Zhang, He Wang