no code implementations • 21 Feb 2024 • Justin Lidard, Haimin Hu, Asher Hancock, Zixu Zhang, Albert Gimó Contreras, Vikash Modi, Jonathan DeCastro, Deepak Gopinath, Guy Rosman, Naomi Leonard, María Santos, Jaime Fernández Fisac
As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic planners versus data-driven policies for safe, interaction-aware motion planning remains an open question.
no code implementations • 3 Feb 2024 • Lianhao Yin, Yutong Ban, Jennifer Eckhoff, Ozanan Meireles, Daniela Rus, Guy Rosman
Understanding and anticipating intraoperative events and actions is critical for intraoperative assistance and decision-making during minimally invasive surgery.
no code implementations • 26 Oct 2023 • Tsun-Hsuan Wang, Alaa Maalouf, Wei Xiao, Yutong Ban, Alexander Amini, Guy Rosman, Sertac Karaman, Daniela Rus
As autonomous driving technology matures, end-to-end methodologies have emerged as a leading strategy, promising seamless integration from perception to control via deep learning.
no code implementations • 28 May 2023 • Justin Lidard, Oswin So, Yanxia Zhang, Jonathan DeCastro, Xiongyi Cui, Xin Huang, Yen-Ling Kuo, John Leonard, Avinash Balachandran, Naomi Leonard, Guy Rosman
Interactions between road agents present a significant challenge in trajectory prediction, especially in cases involving multiple agents.
no code implementations • 29 Mar 2023 • Ameesh Shah, Jonathan DeCastro, John Gideon, Beyazit Yalcinkaya, Guy Rosman, Sanjit A. Seshia
Advancements in simulation and formal methods-guided environment sampling have enabled the rigorous evaluation of machine learning models in a number of safety-critical scenarios, such as autonomous driving.
no code implementations • 8 Mar 2022 • Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh
At a certain time, to forecast a reasonable future trajectory, each agent needs to pay attention to the interactions with only a small group of most relevant agents instead of unnecessarily paying attention to all the other agents.
no code implementations • 27 Feb 2022 • Yutong Ban, Jennifer A. Eckhoff, Thomas M. Ward, Daniel A. Hashimoto, Ozanan R. Meireles, Daniela Rus, Guy Rosman
We constantly integrate our knowledge and understanding of the world to enhance our interpretation of what we see.
no code implementations • 19 Oct 2021 • Yen-Ling Kuo, Xin Huang, Andrei Barbu, Stephen G. McGill, Boris Katz, John J. Leonard, Guy Rosman
Language allows humans to build mental models that interpret what is happening around them resulting in more accurate long-term predictions.
no code implementations • 17 Oct 2021 • Xin Huang, Guy Rosman, Ashkan Jasour, Stephen G. McGill, John J. Leonard, Brian C. Williams
When predicting trajectories of road agents, motion predictors usually approximate the future distribution by a limited number of samples.
1 code implementation • 16 Oct 2021 • Deepak Gopinath, Guy Rosman, Simon Stent, Katsuya Terahata, Luke Fletcher, Brenna Argall, John Leonard
Our model takes as input scene information in the form of a video and noisy gaze estimates, and outputs visual saliency, a refined gaze estimate, and an estimate of the person's attended awareness.
no code implementations • 5 Oct 2021 • Xin Huang, Guy Rosman, Igor Gilitschenski, Ashkan Jasour, Stephen G. McGill, John J. Leonard, Brian C. Williams
Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction.
1 code implementation • 4 Aug 2021 • Xin Huang, Meng Feng, Ashkan Jasour, Guy Rosman, Brian Williams
In this paper, we propose an extension of soft actor critic model to estimate the execution risk of a plan through a risk critic and produce risk-bounded policies efficiently by adding an extra risk term in the loss function of the policy network.
no code implementations • 10 May 2021 • Yutong Ban, Guy Rosman, Jennifer A. Eckhoff, Thomas M. Ward, Daniel A. Hashimoto, Taisei Kondo, Hidekazu Iwaki, Ozanan R. Meireles, Daniela Rus
Comprehension of surgical workflow is the foundation upon which artificial intelligence (AI) and machine learning (ML) holds the potential to assist intraoperative decision-making and risk mitigation.
no code implementations • 24 Nov 2020 • Daisuke Nishiyama, Mario Ynocente Castro, Shirou Maruyama, Shinya Shiroshita, Karim Hamzaoui, Yi Ouyang, Guy Rosman, Jonathan DeCastro, Kuan-Hui Lee, Adrien Gaidon
Automated Vehicles require exhaustive testing in simulation to detect as many safety-critical failures as possible before deployment on public roads.
no code implementations • 11 Nov 2020 • Shinya Shiroshita, Shirou Maruyama, Daisuke Nishiyama, Mario Ynocente Castro, Karim Hamzaoui, Guy Rosman, Jonathan DeCastro, Kuan-Hui Lee, Adrien Gaidon
Traffic simulators are important tools in autonomous driving development.
1 code implementation • 16 Sep 2020 • Boris Ivanovic, Amine Elhafsi, Guy Rosman, Adrien Gaidon, Marco Pavone
Reasoning about human motion is a core component of modern human-robot interactive systems.
no code implementations • 1 Sep 2020 • Yutong Ban, Guy Rosman, Thomas Ward, Daniel Hashimoto, Taisei Kondo, Hidekazu Iwaki, Ozanan Meireles, Daniela Rus
With the understanding of the complete surgical workflow, the robots are able to assist the surgeons in intra-operative events, such as by giving a warning when the surgeon is entering specific keys or high-risk phases.
no code implementations • 29 Aug 2020 • Andreas Bühler, Adrien Gaidon, Andrei Cramariuc, Rares Ambrus, Guy Rosman, Wolfram Burgard
In this work, we propose a behavioral cloning approach that can safely leverage imperfect perception without being conservative.
1 code implementation • 1 Jul 2020 • Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh
To address driving in near-accident scenarios, we propose a hierarchical reinforcement and imitation learning (H-ReIL) approach that consists of low-level policies learned by IL for discrete driving modes, and a high-level policy learned by RL that switches between different driving modes.
no code implementations • 18 Mar 2020 • Xin Huang, Stephen G. McGill, Jonathan A. DeCastro, Luke Fletcher, John J. Leonard, Brian C. Williams, Guy Rosman
Predicting driver intentions is a difficult and crucial task for advanced driver assistance systems.
no code implementations • 14 Dec 2019 • Igor Gilitschenski, Guy Rosman, Arjun Gupta, Sertac Karaman, Daniela Rus
Our main contribution is the concept of learning context maps to improve the prediction task.
no code implementations • 28 Nov 2019 • Xin Huang, Stephen G. McGill, Jonathan A. DeCastro, Luke Fletcher, John J. Leonard, Brian C. Williams, Guy Rosman
Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant systems.
no code implementations • 16 Jan 2019 • Xin Huang, Stephen McGill, Brian C. Williams, Luke Fletcher, Guy Rosman
In this paper, we propose a variational neural network approach that predicts future driver trajectory distributions for the vehicle based on multiple sensors.
no code implementations • 25 Nov 2018 • Alexander Amini, Guy Rosman, Sertac Karaman, Daniela Rus
We define a novel variational network capable of learning from raw camera data of the environment as well as higher level roadmaps to predict (1) a full probability distribution over the possible control commands; and (2) a deterministic control command capable of navigating on the route specified within the map.
no code implementations • 4 Sep 2017 • Guy Rosman, John W. Fisher III, Daniela Rus
We demonstrate the utility of this model for inference tasks such as activity detection, classification, and summarization.
no code implementations • CVPR 2016 • Guy Rosman, Daniela Rus, John W. Fisher III
We then demonstrate how different choices of relevant variable sets (corresponding to the subproblems of locatization and mapping) lead to different criteria for pattern selection and can be computed in an online fashion.
no code implementations • CVPR 2016 • Roy Or - El, Rom Hershkovitz, Aaron Wetzler, Guy Rosman, Alfred M. Bruckstein, Ron Kimmel
The introduction of consumer RGB-D scanners set off a major boost in 3D computer vision research.
no code implementations • CVPR 2015 • Roy Or - El, Guy Rosman, Aaron Wetzler, Ron Kimmel, Alfred M. Bruckstein
The popularity of low-cost RGB-D scanners is increasing on a daily basis.
no code implementations • NeurIPS 2014 • Guy Rosman, Mikhail Volkov, Dan Feldman, John W. Fisher III, Daniela Rus
We consider the problem of computing optimal segmentation of such signals by k-piecewise linear function, using only one pass over the data by maintaining a coreset for the signal.
no code implementations • CVPR 2014 • Randi Cabezas, Oren Freifeld, Guy Rosman, John W. Fisher III
We propose an integrated probabilistic model for multi-modal fusion of aerial imagery, LiDAR data, and (optional) GPS measurements.
no code implementations • CVPR 2014 • Julian Straub, Guy Rosman, Oren Freifeld, John J. Leonard, John W. Fisher III
Traditional approaches to scene representation exploit this phenomenon via the somewhat restrictive assumption that every plane is perpendicular to one of the axes of a single coordinate system.