3 accepted papers
Accurate trajectory prediction is vital for safe autonomous driving, yet existing approaches struggle to balance modeling power and computational efficiency. Attention-based architectures incur quadratic complexity with increasing agents, while recurrent models struggle to capture long-range depende
Motion prediction is crucial for autonomous driving, as it enables accurate forecasting of future vehicle trajectories based on historical inputs. This paper introduces Trajectory Mamba, a novel efficient trajectory prediction framework based on the selective state-space model (SSM). Conventional at…
Magnetic helical miniature robots (MHMRs) exhibit efficient motion performance in low Reynolds number environments, having great promise for biomedical applications like targeted delivery. However, during targeted delivery, the backward propulsion of MHMRs in previous work leads to cargo being relea