7 citations · 19 across the 11 of their papers we have counts for
11 papers
ContraMap: Contrastive Uncertainty Mapping for Robot Environment Representation
Chi Cuong Le, Weiming Zhi
Reliable robot perception requires not only predicting scene structure, but also identifying where predictions should be treated as unreliable due to sparse or missing observations…
Constraining Streaming Flow Models for Adapting Learned Robot Trajectory Distributions
Jieting Long, Dechuan Liu, Weidong Cai +2
Robot motion distributions often exhibit multi-modality and require flexible generative models for accurate representation. Streaming Flow Policies (SFPs) have recently emerged as…
Affordance Transfer Across Object Instances via Semantically Anchored Functional Map
Xiaoxiang Dong, Weiming Zhi
Traditional learning from demonstration (LfD) generally demands a cumbersome collection of physical demonstrations, which can be time-consuming and challenging to scale. Recent adv…
ConEQsA: Concurrent and Asynchronous Embodied Questions Scheduling and Answering
Haisheng Wang, Dong Liu, Weiming Zhi
This paper formulates the Embodied Questions Answering (EQsA) problem, introduces a corresponding benchmark, and proposes an agentic system to tackle the problem. Classical Embodie…
Parallelised Diffeomorphic Sampling-based Motion Planning
Tin Lai, Weiming Zhi, Tucker Hermans +1
We propose Parallelised Diffeomorphic Sampling-based Motion Planning (PDMP). PDMP is a novel parallelised framework that uses bijective and differentiable mappings, or diffeomorphi…
Probabilistic Trajectory Prediction with Structural Constraints
Weiming Zhi, Lionel Ott, Fabio Ramos
This work addresses the problem of predicting the motion trajectories of dynamic objects in the environment. Recent advances in predicting motion patterns often rely on machine lea…
Learning ODEs via Diffeomorphisms for Fast and Robust Integration
Weiming Zhi, Tin Lai, Lionel Ott +2
Advances in differentiable numerical integrators have enabled the use of gradient descent techniques to learn ordinary differential equations (ODEs). In the context of machine lear…
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements
Weiming Zhi, Tin Lai, Lionel Ott +1
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. This pape…
OCTNet: Trajectory Generation in New Environments from Past Experiences
Weiming Zhi, Tin Lai, Lionel Ott +2
Being able to safely operate for extended periods of time in dynamic environments is a critical capability for autonomous systems. This generally involves the prediction and unders…
Occ-Traj120: Occupancy Maps with Associated Trajectories
Tin Lai, Weiming Zhi, Fabio Ramos
Trajectory modelling had been the principal research area for understanding and anticipating human behaviour. Predicting the dynamic path by observing the agent and its surrounding…
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction
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. This requires…