Diffusion-Based Planning

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11 papers in the last four weeks, up 175% on the four weeks before. 0.1% of all new papers.

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Generative Multi-Robot Motion Planning via Diffusion Modeling with Multi-Agent Reinforcement Learning Guidance
May 30, 2026Suk Ki Lee, Venkata Sai Deepak Mutta, Hyunwoong KoMulti-Robot Motion Planning Diffusion-Based Planning
School of Manufacturing Systems and Networks, Arizona State University, Mesa, AZ · Michael W. Hall School of Mechanical Engineering, Mississippi State University, Starkville, MS
Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning
May 30, 2026Byoungwoo Park, Utkarsh A. Mishra, Jaemoo Choi +2Diffusion-Based Planning Long-Horizon Video Generation
KAIST
AR Forcing: Towards Long-Horizon Robot Navigation World Model
May 29, 2026Yifei Yang, Zehua Fan, Huan Li +9World Models for Robotics Autoregressive Diffusion
Institute for AI Industry Research, Tsinghua University · Shanghai Jiao Tong University · School of Safety Science, Tsinghua University +2
Mean-Field Diffuser: Scaling Offline MARL to Thousands of Agents
May 28, 2026Wenhao Li, Xiangfeng Wang, Bo JinMulti-Agent System Optimization Mean Field Games
Tongji University · East China Normal University
Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control
May 28, 2026Hao Ren, Zetong Bi, Yiming Zeng +5Diffusion Model Guidance Diffusion-Based Planning
Sun Yat-sen University, Guangzhou, China · Insta360 Research, Shenzhen, China
Simulation-Informed Diffusion for Decentralized Multi-robot Motion Planning
May 26, 2026Jinhao Liang, Sven Koenig, Ferdinando FiorettoMulti-Robot Motion Planning Constrained Motion Planning
University of Virginia · University of California, Irvine
Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
May 24, 2026Yu Yang, Yihong Guo, Anqi Liu +1Diffusion Model Guidance Reinforcement Learning
Duke University · Johns Hopkins University
Sum of Costs Diffusion with Dynamic Guidance for Motion Planning
May 23, 2026Aysu Aylin Kaplan, Özgür ErkentTrajectory Generation Diffusion-Based Planning
Computer Engineering Department, Hacettepe University, Ankara, Turkey
Anisotropic Diffusion-Driven Ergodic Coverage in Multi-Robot Systems
May 22, 2026Thales C. Silva, Anoop Kiran, Nora AyanianMulti-Robot Systems Diffusion-Based Planning
Department of Computer Science
ChainFlow-VLA: Causal Flow Planning with Vision-Language Models
May 22, 2026Xiyang Wang, Xinlin Wang, Tingguang Zhou +7Trajectory Generation VLMs for Autonomous Driving
1Afari Intelligent Drive · 2Tianjin University · University of Macau
D $^3$ -Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market
May 19, 2026Taijie Chen, Rui Su, Siyuan Feng +6Diffusion-Based Planning Sequential Decision Making
University of Hong Kong · Harbin Institute of Technology · Hong Kong Polytechnic University +1
Plan First, Diffuse Later: Extrinsic Graph Guidance for Long-Horizon Diffusion Planning
May 16, 2026Yaniv Hassidof, Adir Morgan, Yilun Du +1Trajectory Generation Diffusion-Based Planning
Technion · Harvard
DriveSafer: End-to-End Autonomous Driving with Safety Guidance
May 16, 2026Shounak Sural, Raj RajkumarEnd-to-End Autonomous Driving Diffusion-Based Planning
Carnegie Mellon University Pittsburgh, PA
Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making
May 15, 2026Fan Feng, Selena Ge, Minghao Fu +6Latent Action Learning Latent Dynamics Modeling
University of California San Diego · MBZUAI · Carnegie Mellon University +2
Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention
May 13, 2026Yuanzhe Wang, Tian Zhi, Zihang Wei +8Multi-Agent System Optimization Diffusion-Based Planning
State Key Lab of Processors, Institute of Computing Technology, CAS · School of Advanced Interdisciplinary Sciences, CAS · University of Chinese Academy of Sciences +1
The DAWN of World-Action Interactive Models
May 12, 2026Hongbo Lu, Liang Yao, Chenghao He +6Diffusion-Based Planning World Model-Based Planning
1COWARobot Co. Ltd · 2Shanghai Jiao Tong University · 3Hohai University
CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving
May 11, 2026Minqing Huang, Yujiao Xiang, Zihan Liang +7VLMs for Autonomous Driving Diffusion-Based Planning
Afari Intelligent Drive · University of Electronic Science and Technology of China · Shanghai Jiao Tong University +2
Muninn: Your Trajectory Diffusion Model But Faster
May 11, 2026Gokul Puthumanaillam, Hao Jiang, Ruben Hernandez +4Trajectory Generation Diffusion-Based Planning
University of Illinois Urbana-Champaign. · Florida International University. · Providence College.
Latency Analysis and Optimization of Alpamayo 1 via Efficient Trajectory Generation
May 9, 2026Yunseong Jeon, Namcheol Lee, Yoonsu Lee +4Efficient Inference End-to-End Autonomous Driving
Graduate School of Automobile and Mobility, Kookmin University, Seoul, Republic of Korea · Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
HDFlow: Hierarchical Diffusion-Flow Planning for Long-horizon Tasks
May 6, 2026Nandiraju Gireesh, Yuanliang Ju, Chaoyi Xu +3Hierarchical Planning Long-Horizon Robotic Manipulation
1Peking University · University of Toronto. · 2Galbot
Refining Compositional Diffusion for Reliable Long-Horizon Planning
May 4, 2026Kyowoon Lee, Yunhao Luo, Anh Tong +1Trajectory Generation Diffusion-Based Planning
KAIST · University of Michigan · Korea University +1
Decoupled Guidance Diffusion for Adaptive Offline Safe Reinforcement Learning
May 4, 2026Rufeng Chen, Zhaofan Zhang, Zhejiang Yang +2Diffusion-Based Planning Diffusion Guidance
1The Hong Kong University of Science and Technology (Guangzhou) · 2Jilin University
Action Agent: Agentic Video Generation Meets Flow-Constrained Diffusion
May 2, 2026Jeffrin Sam, Nguyen Khang, Yara Mahmoud +2Trajectory Generation Diffusion-Based Planning
Intelligent Space Robotics Laboratory, Skoltech, Bolshoy Boulevard, 30, Moscow 121205, Russia
Probing Visual Planning in Image Editing Models
Apr 23, 2026Zhimu Zhou, Yanpeng Zhao, Qiuyu Liao +2Visual Spatial Reasoning Diffusion-Based Planning
1Shanghai Jiao Tong University · 3State Key Laboratory of General Artificial Intelligence, BIGAI · 2Renmin University of China
MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting
Apr 23, 2026Yining Xing, Zehong Ke, Yiqian Tu +3Trajectory Generation Diffusion-Based Planning
School of Vehicle and Mobility, Tsinghua University, Beijing, China · State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University, Beijing, China
RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework
Apr 16, 2026Hao Gao, Shaoyu Chen, Yifan Zhu +4Diffusion-Based Planning RL for Diffusion Models
Huazhong University of Science & Technology · Horizon Robotics
PC-Diffuser: Path-Consistent Capsule CBF Safety Filtering for Diffusion-Based Trajectory Planner
Mar 11, 2026Eugene Ku, Yiwei LyuConstrained Motion Planning Trajectory Generation
Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
EmbodiedDiffusion: End-to-End Traversability-Guided Visual Diffusion for Heterogeneous Robot Navigation
Dec 2, 2025Iana Zhura, Sausar Karaf, Faryal Batool +7Visual Navigation Trajectory Generation
Intelligent Space Robotics Laboratory, Center for Digital Engineering, Skolkovo Institute of Science and Technology.
DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
Jul 5, 2025Ziying Song, Lin Liu, Hongyu Pan +7End-to-End Autonomous Driving Diffusion-Based Planning
Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence, School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China · School of Artificial Intelligence (School of Software), Yanshan University, Qinhuangdao, China · Horizon Robotics +3
D4orm: Multi-Robot Trajectories with Dynamics-aware Diffusion Denoised Deformations
Mar 15, 2025Yuhao Zhang, Keisuke Okumura, Heedo Woo +2Multi-Robot Motion Planning Constrained Motion Planning
University of Cambridge · UK · National Institute of Advanced Industrial Science and Technology (AIST) +1

May 30, 2026, cs.ROJ/K move · Enter open · S save

Generative Multi-Robot Motion Planning via Diffusion Modeling with Multi-Agent Reinforcement Learning Guidance

Suk Ki Lee, Venkata Sai Deepak Mutta, Hyunwoong Ko

School of Manufacturing Systems and Networks, Arizona State University, Mesa, AZ · Michael W. Hall School of Mechanical Engineering, Mississippi State University, Starkville, MS

Multi-Robot Motion Planning Diffusion-Based Planning Multi-Robot Coordination

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Coordinating multiple robots in shared environments requires generating feasible trajectories for each agent while accounting for interactions among agents. Centralized planning approaches become difficult to scale as the number of robots increases, while decentralized approaches that allow each agent to plan independently do not inherently account for inter-agent interactions. This paper presents a framework for coordinated multi-robot motion planning that combines decentralized generative trajectory planning with multi-agent reinforcement learning (MARL)-based coordination. Each robot independently generates candidate trajectories using a diffusion model trained on single-agent motion data, leveraging the generative model's ability to produce feasible and diverse trajectories. To reduce conflicts between agents, a centralized value function trained via MARL guides the reverse diffusion process through gradient-based steering, enabling interaction-aware trajectory generation without centralized joint planning or retraining of the generative model. This guidance follows an exponential tilting formulation, in which the value function biases the denoising distribution toward trajectories with higher expected multi-agent return. The framework is evaluated in a simulated maze environment with four mobile robots. Experimental results show that the proposed value-guided diffusion planning reduces the inter-agent interference rate from 55.4% to 41.8%, demonstrating that coordination can be effectively achieved while preserving the scalability of decentralized trajectory generation. These results suggest that MARL-based value guidance can effectively introduce coordination into decentralized generative planners without requiring a fully joint multi-robot model.

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