16 citations · 47 across the 16 of their papers we have counts for
17 papers
Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov +1
We present a novel observation about the behavior of offline reinforcement learning (RL) algorithms: on many benchmark datasets, offline RL can produce well-performing and safe pol…
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
Anqi Li, Byron Boots, Ching-An Cheng
We study a new paradigm for sequential decision making, called offline policy learning from observations (PLfO). Offline PLfO aims to learn policies using datasets with substandard…
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
Xiangyun Meng, Nathan Hatch, Alexander Lambert +11
Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structure…
Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior
Karl Van Wyk, Mandy Xie, Anqi Li +9
Classical mechanical systems are central to controller design in energy shaping methods of geometric control. However, their expressivity is limited by position-only metrics and th…
Imitation Learning via Simultaneous Optimization of Policies and Auxiliary Trajectories
Mandy Xie, Anqi Li, Karl Van Wyk +3
Imitation learning (IL) is a frequently used approach for data-efficient policy learning. Many IL methods, such as Dataset Aggregation (DAgger), combat challenges like distribution…
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning
Julen Urain, Anqi Li, Puze Liu +2
Reactive motion generation problems are usually solved by computing actions as a sum of policies. However, these policies are independent of each other and thus, they can have conf…
RMP2: A Structured Composable Policy Class for Robot Learning
Anqi Li, Ching-An Cheng, M. Asif Rana +4
We consider the problem of learning motion policies for acceleration-based robotics systems with a structured policy class specified by RMPflow. RMPflow is a multi-task control fra…
Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees
M. Asif Rana, Anqi Li, Dieter Fox +3
Generating robot motion that fulfills multiple tasks simultaneously is challenging due to the geometric constraints imposed by the robot. In this paper, we propose to solve multi-t…
Optimization Fabrics for Behavioral Design
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie +2
A common approach to the provably stable design of reactive behavior, exemplified by operational space control, is to reduce the problem to the design of virtual classical mechanic…
Geometric Fabrics for the Acceleration-based Design of Robotic Motion
Mandy Xie, Karl Van Wyk, Anqi Li +5
This paper describes the pragmatic design and construction of geometric fabrics for shaping a robot's task-independent nominal behavior, capturing behavioral components such as obs…
Generalized Nonlinear and Finsler Geometry for Robotics
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie +2
Robotics research has found numerous important applications of Riemannian geometry. Despite that, the concept remain challenging to many roboticists because the background material…
Optimization Fabrics
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie +2
This paper presents a theory of optimization fabrics, second-order differential equations that encode nominal behaviors on a space and can be used to define the behavior of a smoot…
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems
Muhammad Asif Rana, Anqi Li, Dieter Fox +3
Robotic tasks often require motions with complex geometric structures. We present an approach to learn such motions from a limited number of human demonstrations by exploiting the…
Inferring and Learning Multi-Robot Policies by Observing an Expert
Pietro Pierpaoli, Harish Ravichandar, Nicholas Waytowich +3
We present a technique for learning how to solve a multi-robot mission that requires interaction with an external environment by observing an expert system executing the same missi…
A Sequential Composition Framework for Coordinating Multi-Robot Behaviors
Pietro Pierpaoli, Anqi Li, Mohit Srinivasan +3
A number of coordinated behaviors have been proposed for achieving specific tasks for multi-robot systems. However, since most applications require more than one such behavior, one…
Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks
Anqi Li, Ching-An Cheng, Byron Boots +1
Robotic systems often need to consider multiple tasks concurrently. This challenge calls for controller synthesis algorithms that fulfill multiple control specifications while main…
Multi-Objective Policy Generation for Multi-Robot Systems Using Riemannian Motion Policies
Anqi Li, Mustafa Mukadam, Magnus Egerstedt +1
In many applications, multi-robot systems are required to achieve multiple objectives. For these multi-objective tasks, it is oftentimes hard to design a single control policy that…