activity
20182023
most citedLyapunov-based Safe Policy Optimization for Continuous Control

154 citations · 177 across the 12 of their papers we have counts for

collaborators
Showing cs.ROShow all

13 papers · 1 filter

cs.RO2021

AutoPilot: Automating SoC Design Space Exploration for SWaP Constrained Autonomous UAVs

Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj +6

Building domain-specific accelerators for autonomous unmanned aerial vehicles (UAVs) is challenging due to a lack of systematic methodology for designing onboard compute. Balancing…

cs.RO2020

Visual Navigation Among Humans with Optimal Control as a Supervisor

Varun Tolani, Somil Bansal, Aleksandra Faust +1

Real world visual navigation requires robots to operate in unfamiliar, human-occupied dynamic environments. Navigation around humans is especially difficult because it requires ant…

cs.RO2019

Learned Critical Probabilistic Roadmaps for Robotic Motion Planning

Brian Ichter, Edward Schmerling, Tsang-Wei Edward Lee +1

Sampling-based motion planning techniques have emerged as an efficient algorithmic paradigm for solving complex motion planning problems. These approaches use a set of probing samp…

cs.RO2019

Neural Collision Clearance Estimator for Batched Motion Planning

J. Chase Kew, Brian Ichter, Maryam Bandari +2

We present a neural network collision checking heuristic, ClearanceNet, and a planning algorithm, CN-RRT. ClearanceNet learns to predict separation distance (minimum distance betwe…

cs.RO2019

Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller

Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz +5

We present fully autonomous source seeking onboard a highly constrained nano quadcopter, by contributing application-specific system and observation feature design to enable infere…

cs.RO2019

RL-RRT: Kinodynamic Motion Planning via Learning Reachability Estimators from RL Policies

Hao-Tien Lewis Chiang, Jasmine Hsu, Marek Fiser +2

This paper addresses two challenges facing sampling-based kinodynamic motion planning: a way to identify good candidate states for local transitions and the subsequent computationa…