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Multi-Objective Trajectory Planning with Dual-Encoder

2024-03-26 · Beibei Zhang, Tian Xiang, Chentao Mao, Yuhua Zheng, Shuai Li, Haoyi Niu, Xiangming Xi, Wenyuan Bai, Feng Gao

Time-jerk optimal trajectory planning is crucial in advancing robotic arms' performance in dynamic tasks. Traditional methods rely on solving complex nonlinear programming problems, bringing significant delays in generating optimized trajectories. In this paper, we propose a two-stage approach to accelerate time-jerk optimal trajectory planning. Firstly, we introduce a dual-encoder based transformer model to establish a good preliminary trajectory. This trajectory is subsequently refined through sequential quadratic programming to improve its optimality and robustness. Our approach outperforms the state-of-the-art by up to 79.72\% in reducing trajectory planning time. Compared with existing methods, our method shrinks the optimality gap with the objective function value decreasing by up to 29.9\%.

📄 PDF Abstract BibTeX arXiv:2403.17353

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Trajectory Planning

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings

2018-06-07 · ICML 2018 7 · John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach 외

In this work, we take a representation learning perspective on hierarchical reinforcement learning, where the problem of learning lower layers in a hierarchy is transformed into the problem of learning trajectory-level g…

Hierarchical Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)+1

Trajectory Planning with Deep Reinforcement Learning in High-Level Action Spaces

2021-09-30 · Kyle R. Williams, Rachel Schlossman, Daniel Whitten, Joe Ingram 외

This paper presents a technique for trajectory planning based on continuously parameterized high-level actions (motion primitives) of variable duration. This technique leverages deep reinforcement learning (Deep RL) to f…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning (RL)Trajectory Planning+1

Optimization-based Safe Trajectory Planning for Autonomous Ground Vehicle in Multi-Floor Scenarios

2026-06-23 · Zishang Xiang, Runda Zhang, Runqi Chai, Kaiyuan Chen 외 arxiv

The development of trajectory planning strategies for autonomous ground vehicles (AGVs) represents a prevailing research interest within the domain of intelligent transportation systems. This paper introduces a trajector…

Trajectory Planning

Social-DualCVAE: Multimodal Trajectory Forecasting Based on Social Interactions Pattern Aware and Dual Conditional Variational Auto-Encoder

2022-02-08 · Jiashi Gao, Xinming Shi, James J. Q. Yu

Pedestrian trajectory forecasting is a fundamental task in multiple utility areas, such as self-driving, autonomous robots, and surveillance systems. The future trajectory forecasting is multi-modal, influenced by physic…

Trajectory Forecasting Trajectory Prediction

Distilling Multi-modal Large Language Models for Autonomous Driving

2025-01-16 · CVPR 2025 1 · Deepti Hegde, Rajeev Yasarla, Hong Cai, Shizhong Han 외

Autonomous driving demands safe motion planning, especially in critical "long-tail" scenarios. Recent end-to-end autonomous driving systems leverage large language models (LLMs) as planners to improve generalizability to…

Autonomous Driving Motion Planning World Knowledge