Travelled to:1 × Sweden
1 × Taiwan
Collaborated with:K.Goldberg R.Fox J.Mahler S.Krishnan J.Lee Caleb Chuck Xinhe Ren D.Wang F.T.Pokorny S.Patil P.Abbeel Carolyn Chen Jacky Liang Pusong Li Ruta Joshi Hankun Zhao Andrew Cui Schuyler A. Cullen Brian Paden David V. Gealy Wesley Yu-Shu Hsieh Anca D. Dragan Z.McCarthy J.P.v.d.Berg D.Kragic Benno Staub Ajay Kumar Tanwani Michel Breyer Yutaka Takaoka Max Bajracharya R.Siegwart S.Sen A.Murali B.Kehoe J.Wang M.Franklin K.Y.Goldberg
Talks about:learn (6) demonstr (4) robot (4) grasp (3) deep (3) use (3) manipul (2) clean (2) autom (2) task (2)
Person: Michael Laskey
DBLP: Laskey:Michael
Contributed to:
201520142016201720182019Wrote 10 papers:
- CASE-2015-LaskeyMMPPBKAG #2d #modelling #multi #nondeterminism
- Multi-armed bandit models for 2D grasp planning with uncertainty (ML, JM, ZM, FTP, SP, JPvdB, DK, PA, KG), pp. 572–579.
- CASE-2014-MahlerKLSMKPWFAG #learning #process #using
- Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression (JM, SK, ML, SS, AM, BK, SP, JW, MF, PA, KYG), pp. 532–539.
- CASE-2016-LaskeyLCGHPDG #learning #using
- Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations (ML, JL, CC, DVG, WYSH, FTP, ADD, KG), pp. 827–834.
- CASE-2017-ChenKLFG #algorithm #case study #education #user study
- An algorithm and user study for teaching bilateral manipulation via iterated best response demonstrations (CC, SK, ML, RF, KG), pp. 151–158.
- CASE-2017-ChuckLKJFG #automation #learning #statistics
- Statistical data cleaning for deep learning of automation tasks from demonstrations (CC, ML, SK, RJ, RF, KG), pp. 1142–1149.
- CASE-2017-LiangMLLG #automation #industrial #learning #using
- Using dVRK teleoperation to facilitate deep learning of automation tasks for an industrial robot (JL, JM, ML, PL, KG), pp. 1–8.
- CASE-2018-LeeLFG #constraints #estimation #learning
- Constraint Estimation and Derivative-Free Recovery for Robot Learning from Demonstrations (JL, ML, RF, KG), pp. 270–277.
- CASE-2018-RenWLG #behaviour #learning #online #video
- Learning Traffic Behaviors by Extracting Vehicle Trajectories from Online Video Streams (XR, DW, ML, KG), pp. 1276–1283.
- CASE-2018-ZhaoCCPLG #first-order #lightweight #named
- FLUIDS: A First-Order Lightweight Urban Intersection Driving Simulator (HZ, AC, SAC, BP, ML, KG), pp. 697–704.
- CASE-2019-StaubTMBLTBSG #mobile
- Dex-Net MM: Deep Grasping for Surface Decluttering with a Low-Precision Mobile Manipulator (BS, AKT, JM, MB, ML, YT, MB, RS, KG), pp. 1373–1379.