no code implementations • 10 Feb 2025 • Ola Shorinwa, Jiankai Sun, Mac Schwager, Anirudha Majumdar
We present SIREN for registration of multi-robot Gaussian Splatting (GSplat) maps, with zero access to camera poses, images, and inter-map transforms for initialization or fusion of local submaps.
no code implementations • 20 Dec 2024 • JunEn Low, Maximilian Adang, Javier Yu, Keiko Nagami, Mac Schwager
We propose a new simulator, training approach, and policy architecture, collectively called SOUS VIDE, for end-to-end visual drone navigation.
no code implementations • 20 Nov 2024 • Ola Shorinwa, Jiankai Sun, Mac Schwager
We present FAST-Splat for fast, ambiguity-free semantic Gaussian Splatting, which seeks to address the main limitations of existing semantic Gaussian Splatting methods, namely: slow training and rendering speeds; high memory usage; and ambiguous semantic object localization.
1 code implementation • 16 Sep 2024 • Chan Kim, Keonwoo Kim, Mintaek Oh, Hanbi Baek, Jiyang Lee, Donghwi Jung, Soojin Woo, Younkyung Woo, John Tucker, Roya Firoozi, Seung-Woo Seo, Mac Schwager, Seong-Woo Kim
Given that real-world environments are inherently stochastic, initial plans based solely on LLMs' general knowledge may fail to achieve their objectives, unlike in static scenarios.
no code implementations • 28 Aug 2024 • Carlos Plou, Pablo Pueyo, Ruben Martinez-Cantin, Mac Schwager, Ana C. Murillo, Eduardo Montijano
Gen-Swarms is an innovative method that leverages and combines the capabilities of deep generative models with reactive navigation algorithms to automate the creation of drone shows.
1 code implementation • 8 May 2024 • Joseph A. Vincent, Haruki Nishimura, Masha Itkina, Paarth Shah, Mac Schwager, Thomas Kollar
To rigorously evaluate behavior cloning policies, we present a framework that provides a tight lower-bound on robot performance in an arbitrary environment, using a minimal number of experimental policy rollouts.
1 code implementation • 7 May 2024 • Ola Shorinwa, Johnathan Tucker, Aliyah Smith, Aiden Swann, Timothy Chen, Roya Firoozi, Monroe Kennedy III, Mac Schwager
ASK-Splat enables geometric, semantic, and affordance understanding of 3D scenes, which is critical in many robotics tasks; (ii) SEE-Splat, a real-time scene-editing module using 3D semantic masking and infilling to visualize the motions of objects that result from robot interactions in the real-world.
no code implementations • 20 Mar 2024 • Pablo Pueyo, Eduardo Montijano, Ana C. Murillo, Mac Schwager
A formation is visually represented through alpha-shape contours and the most representative color is automatically found for the input word.
no code implementations • 14 Mar 2024 • Aiden Swann, Matthew Strong, Won Kyung Do, Gadiel Sznaier Camps, Mac Schwager, Monroe Kennedy III
Optical tactile sensors have become widespread in their use in robotics for manipulation and object representation; however, raw optical tactile sensor data is unsuitable to directly supervise a 3DGS scene.
no code implementations • 11 Nov 2023 • Jiankai Sun, Jianing Qiu, Chuanyang Zheng, John Tucker, Javier Yu, Mac Schwager
The construction of a NeRF-like model from an egocentric image sequence plays a pivotal role in understanding human behavior and holds diverse applications within the realms of VR/AR.
1 code implementation • 31 Oct 2023 • Kyle Brown, Dylan M. Asmar, Mac Schwager, Mykel J. Kochenderfer
Mobile autonomous robots have the potential to revolutionize manufacturing processes.
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.
no code implementations • 18 Jan 2023 • Patrick H. Washington, David Fridovich-Keil, Mac Schwager
In this paper, we introduce GrAVITree, a tree- and sampling-based algorithm to compute a near-optimal value function and corresponding feedback policy for indefinite time-horizon, terminal state-constrained nonlinear optimal control problems.
1 code implementation • 17 Oct 2022 • Simon Le Cleac'h, Hong-Xing Yu, Michelle Guo, Taylor A. Howell, Ruohan Gao, Jiajun Wu, Zachary Manchester, Mac Schwager
A robot can use this simulation to optimize grasps and manipulation trajectories of neural objects, or to improve the neural object models through gradient-based real-to-simulation transfer.
1 code implementation • 15 Oct 2022 • Joseph A. Vincent, Mac Schwager
In our examples we demonstrate the ability of our approach to find non-convex control invariant sets and ROAs on tasks with learned van der Pol oscillator and pendulum models.
no code implementations • 24 Sep 2022 • Jiankai Sun, Yan Xu, Mingyu Ding, Hongwei Yi, Chen Wang, Jingdong Wang, Liangjun Zhang, Mac Schwager
Using current NeRF training tools, a robot can train a NeRF environment model in real-time and, using our algorithm, identify 3D bounding boxes of objects of interest within the NeRF for downstream navigation or manipulation tasks.
1 code implementation • 23 Nov 2020 • Joseph A. Vincent, Mac Schwager
We present a method for computing exact reachable sets for deep neural networks with rectified linear unit (ReLU) activation.
no code implementations • NeurIPS Workshop LMCA 2020 • Abhishek Cauligi, Preston Culbertson, Mac Schwager, Bartolomeo Stellato, Marco Pavone
Mixed-integer convex programming (MICP) is a popular modeling framework for solving discrete and combinatorial optimization problems arising in various settings.
no code implementations • 12 Sep 2020 • Haruki Nishimura, Boris Ivanovic, Adrien Gaidon, Marco Pavone, Mac Schwager
This paper presents a novel online framework for safe crowd-robot interaction based on risk-sensitive stochastic optimal control, wherein the risk is modeled by the entropic risk measure.
no code implementations • 1 Jul 2020 • Ransalu Senanayake, Maneekwan Toyungyernsub, Mingyu Wang, Mykel J. Kochenderfer, Mac Schwager
We can use driving data collected over a long period of time to extract rich information about how vehicles behave in different areas of the roads.
1 code implementation • 16 Jun 2020 • Kyle Brown, Oriana Peltzer, Martin A. Sehr, Mac Schwager, Mykel J. Kochenderfer
We study the problem of sequential task assignment and collision-free routing for large teams of robots in applications with inter-task precedence constraints (e. g., task $A$ and task $B$ must both be completed before task $C$ may begin).
2 code implementations • 17 Mar 2020 • Pablo Pueyo, Eric Cristofalo, Eduardo Montijano, Mac Schwager
Drones and Unmanned Aerial Vehicles (UAV's) are becoming increasingly popular in the film and entertainment industries in part because of their maneuverability and the dynamic shots and perspectives they enable.
Robotics
2 code implementations • 12 Mar 2020 • Ratnesh Madaan, Nicholas Gyde, Sai Vemprala, Matthew Brown, Keiko Nagami, Tim Taubner, Eric Cristofalo, Davide Scaramuzza, Mac Schwager, Ashish Kapoor
Autonomous drone racing is a challenging research problem at the intersection of computer vision, planning, state estimation, and control.
1 code implementation • 22 Oct 2019 • Simon Le Cleac'h, Mac Schwager, Zachary Manchester
We evaluate our solver in the context of autonomous driving on scenarios with a strong level of interactions between the vehicles.
1 code implementation • 30 May 2019 • Guillermo Angeris, Kunal Shah, Mac Schwager
We present a fully distributed collision avoidance algorithm based on convex optimization for a team of mobile robots.
Optimization and Control Robotics
1 code implementation • 8 Jan 2018 • Riccardo Spica, Davide Falanga, Eric Cristofalo, Eduardo Montijano, Davide Scaramuzza, Mac Schwager
To be successful in multi-player drone racing, a player must not only follow the race track in an optimal way, but also compete with other drones through strategic blocking, faking, and opportunistic passing while avoiding collisions.
Robotics
no code implementations • 23 Sep 2016 • Derya Aksaray, Austin Jones, Zhaodan Kong, Mac Schwager, Calin Belta
This paper addresses the problem of learning optimal policies for satisfying signal temporal logic (STL) specifications by agents with unknown stochastic dynamics.
Systems and Control
no code implementations • 9 Sep 2013 • Austin Jones, Mac Schwager, Calin Belta
We present a new temporal logic called Distribution Temporal Logic (DTL) defined over predicates of belief states and hidden states of partially observable systems.