Search Results for author: Weiming Zhi

Found 9 papers, 0 papers with code

L4KDE: Learning for KinoDynamic Tree Expansion

no code implementations2 Mar 2022 Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos

We study the kinodynamic variants of tree-based planning, where we have known system dynamics and kinematic constraints.

Motion Planning

Learning Efficient and Robust Ordinary Differential Equations via Diffeomorphisms

no code implementations29 Sep 2021 Weiming Zhi, Tin Lai, Lionel Ott, Edwin V Bonilla, Fabio Ramos

Consequently, by restricting the base ODE to be amenable to integration, we can speed up and improve the robustness of integrating trajectories from the learned system.

Probabilistic Trajectory Prediction with Structural Constraints

no code implementations9 Jul 2021 Weiming Zhi, Lionel Ott, Fabio Ramos

This distribution is then used as a prior to a constrained optimisation problem which enforces chance constraints on the trajectory distribution.

Trajectory Prediction

Learning ODEs via Diffeomorphisms for Fast and Robust Integration

no code implementations4 Jul 2021 Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos

Advances in differentiable numerical integrators have enabled the use of gradient descent techniques to learn ordinary differential equations (ODEs).

Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements

no code implementations12 Nov 2020 Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos

Critical for the coexistence of humans and robots in dynamic environments is the capability for agents to understand each other's actions, and anticipate their movements.

OCTNet: Trajectory Generation in New Environments from Past Experiences

no code implementations25 Sep 2019 Weiming Zhi, Tin Lai, Lionel Ott, Gilad Francis, Fabio Ramos

This generally involves the prediction and understanding of motion patterns of dynamic entities, such as vehicles and people, in the surroundings.

motion prediction

Occ-Traj120: Occupancy Maps with Associated Trajectories

no code implementations5 Sep 2019 Tin Lai, Weiming Zhi, Fabio Ramos

Trajectory modelling had been the principal research area for understanding and anticipating human behaviour.

Autonomous Driving

Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction

no code implementations11 Jul 2019 Weiming Zhi, Lionel Ott, Fabio Ramos

Understanding the dynamics of an environment, such as the movement of humans and vehicles, is crucial for agents to achieve long-term autonomy in urban environments.

motion prediction

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