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Ahalya Prabhakar

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Related publications (5)

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Mechanical intelligence for learning embodied sensor-object relationships

Ahalya Prabhakar

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

Nature Portfolio2022

A Predictive Model for Tactile Force Estimation Using Audio-Tactile Data

Dominic Reber, Aude Billard, Ahalya Prabhakar, Loïc Niederhauser

Robust in-hand manipulation of objects with movable content requires estimation and prediction of the contents' motion with enough anticipation to allow time to compensate for resulting internal torques. The quick estimation of the objects' dynamics can be ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Credit Assignment Safety Learning from Human Demonstrations

Aude Billard, Ahalya Prabhakar

A critical need in assistive robotics, such as assistive wheelchairs for navigation, is a need to learn task intent and safety guarantees through user interactions in order to ensure safe task performance. For tasks where the objectives from the user are n ...

2021

Multimodal Sensory Learning for Real-time, Adaptive Manipulation

Aude Billard, Ahalya Prabhakar

Adaptive control for real-time manipulation requires quick estimation and prediction of object properties. While robot learning in this area primarily focuses on using vision, many tasks cannot rely on vision due to object occlusion. Here, we formulate a l ...

2021

User-specific, Adaptable Safety Controllers Facilitate User Adoption in Human-Robot Collaboration

Aude Billard, Ahalya Prabhakar

As assistive and collaborative robots become more ubiquitous in the real-world, we need to develop interfaces and controllers that are safe for users to build trust and encourage adoption. In this Blue Sky paper, we discuss the need for co-evolving task an ...

2022