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Brian Cera

4 accepted papers

2023

MotionLM: Multi-Agent Motion Forecasting as Language Modeling

ICCV 2023poster

Reliable forecasting of the future behavior of road agents is a critical component to safe planning in autonomous vehicles. Here, we represent continuous trajectories as sequences of discrete motion tokens and cast multi-agent motion prediction as a language modeling task over this domain. Our model…

Cited by 104PDF ↗Scholar ↗
2018

Multi-Cable Rolling Locomotion with Spherical Tensegrities Using Model Predictive Control and Deep Learning

IROS 2018poster

This work presents a model-based approach for creating robust control policies for rolling locomotion with a spherical tensegrity topology. Utilizing the structured dynamics of Class-1 tensegrity systems, we turn to model predictive control (MPC) to generate optimal multi-cable actuation trajectorie…

Cited by 32Source ↗Scholar ↗
2017

Inclined surface locomotion strategies for spherical tensegrity robots

IROS 2017poster

This paper presents a new teleoperated spherical tensegrity robot capable of performing locomotion on steep inclined surfaces. With a novel control scheme centered around the simultaneous actuation of multiple cables, the robot demonstrates robust climbing on inclined surfaces in hardware experiment…

Cited by 44Source ↗Scholar ↗
2016

Hopping and rolling locomotion with spherical tensegrity robots

IROS 2016poster

This work presents a 10 kg tensegrity ball probe that can quickly and precisely deliver a 1 kg payload over a 1 km distance on the Moon by combining cable-driven rolling and thruster-based hopping. Previous research has shown that cable-driven rolling is effective for precise positioning, even in ro…

Cited by 80Source ↗Scholar ↗