no code implementations • 11 Mar 2024 • Roberto Bigazzi, Lorenzo Baraldi, Shreyas Kousik, Rita Cucchiara, Marco Pavone
Robots require a semantic understanding of their surroundings to operate in an efficient and explainable way in human environments.
no code implementations • 14 Sep 2023 • Jiankai Sun, Shreyas Kousik, David Fridovich-Keil, Mac Schwager
Connected autonomous vehicles (CAVs) promise to enhance safety, efficiency, and sustainability in urban transportation.
1 code implementation • 15 Apr 2022 • Mahmoud Selim, Amr Alanwar, Shreyas Kousik, Grace Gao, Marco Pavone, Karl H. Johansson
Reinforcement learning (RL) is capable of sophisticated motion planning and control for robots in uncertain environments.
1 code implementation • 3 Aug 2021 • Shreyas Kousik, Adam Dai, Grace Gao
This paper introduces ellipsotopes, a set representation that is closed under affine maps, Minkowski sums, and intersections.
1 code implementation • 16 Jul 2021 • Long Kiu Chung, Adam Dai, Derek Knowles, Shreyas Kousik, Grace X. Gao
This is because it remains an open challenge to train a neural network to obey safety constraints.
1 code implementation • 3 Mar 2020 • Shreyas Kousik, Bohao Zhang, Pengcheng Zhao, Ram Vasudevan
To move through the world, mobile robots typically use a receding-horizon strategy, wherein they execute an old plan while computing a new plan to incorporate new sensor information.
Optimization and Control Robotics
1 code implementation • 5 Feb 2020 • Patrick Holmes, Shreyas Kousik, Bohao Zhang, Daphna Raz, Corina Barbalata, Matthew Johnson-Roberson, Ram Vasudevan
At runtime, in each receding-horizon planning iteration, ARMTD constructs a reachable set of the entire arm in workspace and intersects it with obstacles to generate sub-differentiable and provably-conservative collision-avoidance constraints on the trajectory parameters.
Robotics
2 code implementations • 11 Apr 2019 • Shreyas Kousik, Patrick Holmes, Ramanarayan Vasudevan
Quadrotors can provide services such as infrastructure inspection and search-and-rescue, which require operating autonomously in cluttered environments.
Robotics Systems and Control
1 code implementation • 5 Feb 2019 • Sean Vaskov, Utkarsh Sharma, Shreyas Kousik, Matthew Johnson-Roberson, Ramanarayan Vasudevan
Trajectory planning is challenging for autonomous cars since they operate in unpredictable environments with limited sensor horizons.
Systems and Control
1 code implementation • 18 Sep 2018 • Shreyas Kousik, Sean Vaskov, Fan Bu, Matthew Johnson-Roberson, Ram Vasudevan
At runtime, the FRS is used to map obstacles to the space of parameterized trajectories, which allows RTD to select a safe trajectory at every planning iteration.
Robotics Systems and Control
2 code implementations • 28 Apr 2017 • Shreyas Kousik, Sean Vaskov, Matthew Johnson-Roberson, Ramanarayan Vasudevan
Path planning for autonomous vehicles in arbitrary environments requires a guarantee of safety, but this can be impractical to ensure in real-time when the vehicle is described with a high-fidelity model.
Systems and Control Robotics