Review of pedestrian trajectory prediction methods: Comparing deep learning and knowledge-based approaches
R Korbmacher, A Tordeux - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
In crowd scenarios, predicting trajectories of pedestrians is a complex and challenging task
depending on many external factors. The topology of the scene and the interactions …
depending on many external factors. The topology of the scene and the interactions …
Learning quadrotor dynamics for precise, safe, and agile flight control
This article reviews the state-of-the-art modeling and control techniques for aerial robots
such as quadrotor systems and presents several future research directions in this area. The …
such as quadrotor systems and presents several future research directions in this area. The …
Chatgpt for robotics: Design principles and model abilities
This paper presents an experimental study regarding the use of OpenAI's ChatGPT for
robotics applications. We outline a strategy that combines design principles for prompt …
robotics applications. We outline a strategy that combines design principles for prompt …
A survey on trajectory-prediction methods for autonomous driving
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
Hivt: Hierarchical vector transformer for multi-agent motion prediction
Accurately predicting the future motions of surrounding traffic agents is critical for the safety
of autonomous vehicles. Recently, vectorized approaches have dominated the motion …
of autonomous vehicles. Recently, vectorized approaches have dominated the motion …
Leapfrog diffusion model for stochastic trajectory prediction
To model the indeterminacy of human behaviors, stochastic trajectory prediction requires a
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …
Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting
Predicting accurate future trajectories of multiple agents is essential for autonomous systems
but is challenging due to the complex interaction between agents and the uncertainty in …
but is challenging due to the complex interaction between agents and the uncertainty in …
Multimodal motion prediction with stacked transformers
Predicting multiple plausible future trajectories of the nearby vehicles is crucial for the safety
of autonomous driving. Recent motion prediction approaches attempt to achieve such …
of autonomous driving. Recent motion prediction approaches attempt to achieve such …
Eqmotion: Equivariant multi-agent motion prediction with invariant interaction reasoning
Learning to predict agent motions with relationship reasoning is important for many
applications. In motion prediction tasks, maintaining motion equivariance under Euclidean …
applications. In motion prediction tasks, maintaining motion equivariance under Euclidean …
Scene transformer: A unified architecture for predicting multiple agent trajectories
Predicting the motion of multiple agents is necessary for planning in dynamic environments.
This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …
This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …