Distance Metrics and Algorithms for Task Space Path Optimization - PowerPoint PPT Presentation

Oct 02, 2022 •259 likes •908 views

Distance Metrics and Algorithms for Task Space Path Optimization Rachel Holladay Siddhartha Srinivasa The Robotics Institute Carnegie Mellon University Goal: Follow End-Effector Path in Task Space Goal: Follow End-Effector Path in Task

Distance Metrics and Algorithms for Task Space Path Optimization Rachel Holladay Siddhartha Srinivasa The Robotics Institute Carnegie Mellon University
Goal: Follow End-Effector Path in Task Space
Goal: Follow End-Effector Path in Task Space subject to constraints.
Goal: Follow a Reference Path
Goal: Follow a Reference Path by leveraging motion planning.
Key Insight Use trajectory optimization to optimize our path to be close to our reference path.
Key Insight Use trajectory optimization to optimize our path to be close to our reference path.
Task Space
Task Space
Task Space
Task Space Configuration Space
Task Space Configuration Space
FK IK Task Space Configuration Space
How to compare the distance between task space paths?
How to compare the distance between task space paths? Borrow from computational geometry.
One-way Hausdorff Distance
One-way Hausdorff Distance
Two-way Hausdorff Distance
Follow Balls in order .
Fréchet Distance
Fréchet Distance
Fréchet Distance
Fréchet Distance
Fréchet Distance
Fréchet Distance
Use the Fréchet Distance to capture the task space distance between paths.
Gradient of Distance Function
Gradient of Distance Function
Gradient of Distance Function
Discrete Fréchet
How can we assist our optimizer?
Use our distance metrics to find the areas that need additional constraints.
Key Insight Use trajectory optimization to optimize our path to be close to our reference path.
Use computational geometry techniques to measure task space distance between paths.
Distance Metrics and Algorithms for Task Space Path Optimization Rachel Holladay Siddhartha Srinivasa https://www.personalrobotics.ri.cmu.edu http://www.andrew.cmu.edu/user/rmh/

Download Presentation

Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Distance in data space Notion of distance (metrics) in data space Who is my closest neighbor?

Fundamentals of AI Introduction and the most basic concepts Distance in data space Notion of distance (metrics) in data space Who is my closest neighbor? Euclidean distance Shape of the 2D sphere, R=1 Euclidean distance Euclidean distance

518 views • 18 slides

Three Graph Algorithms Shortest Distance Paths Distance/Cost of a path in weighted graph sum of

Three Graph Algorithms Shortest Distance Paths Distance/Cost of a path in weighted graph sum of weights of all edges on the path path A, B, E, cost is 2+3=5 path A, B, C, E, cost is 2+1+4=7 How to find shortest distance path from a node

335 views • 6 slides

Distance Metrics Mark Voorhies 4/27/2017 Mark Voorhies Distance Metrics Anatomy of a

Distance Metrics Mark Voorhies 4/27/2017 Mark Voorhies Distance Metrics Anatomy of a Programming Language Mark Voorhies Distance Metrics Anatomy of a Programming Language def f(x,y): f(x) return x*y from math import sqrt functions Mark

625 views • 26 slides

The q -gram distance Bioinformatics Algorithms In many situations, edit distance is a good

The q -gram distance Bioinformatics Algorithms In many situations, edit distance is a good model for di ff erences / (Fundamental Algorithms, module 2) similarity between strings. But sometimes, other distance functions serve the purpose

249 views • 4 slides

Shortest Path Similar Routing 2 A New Metric A new metric path- based metric that can use used

R outing S tate D istance: A Path-based Metric for Network Analysis Gonca Grsun joint work with joint work with Natali Ruchansky, Evimaria Terzi, Mark Crovella Distance Metrics for Analyzing Routing Shortest Path Similar Routing 2 A New

1.43k views • 48 slides

Distance Metrics Mark Voorhies 5/14/2015 Mark Voorhies Distance Metrics New verbs f u n c t i

Distance Metrics Mark Voorhies 5/14/2015 Mark Voorhies Distance Metrics New verbs f u n c t i o n ( parameter1 , parameter2 ) : def Do t h i s ! # Code to do t h i s return r e t u r n v a l u e Mark Voorhies

523 views • 27 slides

BGSU Distance Programs Task Force Report Introduction The Distance Programs Task Force was

BGSU Distance Programs Task Force Report Introduction The Distance Programs Task Force was commissioned by Senior Vice President and Provost for Academic Affairs, Rodney Rogers, under the direction of BGSU President Mary Ellen Mazey. The

466 views • 42 slides

Overview q Routing Algorithms v Link-state From last week v Distance-vector TODAY 2 1

Smith College, CSC 249 March 6, 2018 1 Overview q Routing Algorithms v Link-state From last week v Distance-vector TODAY 2 1 Overview of Routing so far v Routing algorithms v Find the best path through a network v Create

661 views • 9 slides

6.02 Fall 2012 Lecture #7 Viterbi decoding of convolutional codes Path and branch metrics

6.02 Fall 2012 Lecture #7 Viterbi decoding of convolutional codes Path and branch metrics Hard-decision & soft-decision decoding Performance issues: decoder complexity, post- decoding BER, free distance concept 6.02 Fall 2012

488 views • 20 slides

Configuration Space Configuration Space NUS CS 5247 David Hsu What is a path? 2 Rough idea

Configuration Space Configuration Space NUS CS 5247 David Hsu What is a path? 2 Rough idea Convert rigid robots, articulated robots, etc. into points Apply algorithms for moving points 3 Mapping from the workspace to the

1.17k views • 28 slides

Fast Shortest Path Distance Estimation in Large Networks Michalis Potamias Francesco

Fast Shortest Path Distance Estimation in Large Networks Michalis Potamias Francesco Bonchi Carlos Castillo Aristides Gionis Context-aware Search use shortest-path distance in wikipedia links-graph! S h o r t e s t

685 views • 19 slides

Partial-Order Planning 1 State-Space vs. Plan-Space State-space ( situation space ) planning

Partial-Order Planning 1 State-Space vs. Plan-Space State-space ( situation space ) planning algorithms search through the space of possible states of the world searching for a path that solves the problem. They can be based on

759 views • 13 slides

Results of the WMT19 Metrics Shared Task Segment-Level and Strong MT Systems Pose Big Challenges

Results of the WMT19 Metrics Shared Task Segment-Level and Strong MT Systems Pose Big Challenges Qingsong Ma Johnny Tian-Zheng Wei Ond rej Bojar Yvette Graham 1 / 31 Overview Overview of Metrics Task Updates to Metric Task in

554 views • 40 slides

Results of the WMT16 Metrics Shared Task Ond rej Bojar Yvette Graham Amir Kamran Milo s

Results of the WMT16 Metrics Shared Task Ond rej Bojar Yvette Graham Amir Kamran Milo s Stanojevi c WMT16, Aug 11, 2016 1 / 32 Overview Summary of Metrics Task. Updates to Metric Task in 2016. Results 2 / 32 Metrics

634 views • 45 slides

A * A path finding algorithm. A path finding algorithm. Given a state space, such as a

A * A path finding algorithm. A path finding algorithm. Given a state space, such as a 2-dimensional map, find a path from point A to point B in that space, if such a path exists. If such a path exists, return a path within certain criteria

445 views • 30 slides

Path algorithms Geoff Gordon & Ryan Tibshirani Optimization 10-725 / 36-725 1 Path

Path algorithms Geoff Gordon & Ryan Tibshirani Optimization 10-725 / 36-725 1 Path algorithms In this lecture we consider problems of the form x R n g ( x ) + h ( x ) min where 0 . In particular, well look at path

715 views • 23 slides

LNG Fuelled Vessels: Where are we? Summary Intro Where are we? The Shipping Worlds

LNG Fuelled Vessels: Where are we? Summary Intro Where are we? The Shipping Worlds perspective Where are we? The Rosetti Marino Yard and UNIGEs perspective Training needs Conclusions SHIPBUILDI ILDING Harb

815 views • 35 slides

Swedish part of ARISS Contact from Sand Sand Sweden The Swedish part of ARISS contact will

Sand Sweden Swedish part of ARISS Contact from Sand Sand Sweden The Swedish part of ARISS contact will be done from Sand isle and is located about 250 miles (400 Km) north from Stockholm. Sand Sweden Three different types of

367 views • 15 slides

Minerals for a Pd Clean air sustainable future Li Electric cars Si Renewable energy 1

Ti Pt Lighter aircrafts Minerals for a Pd Clean air sustainable future Li Electric cars Si Renewable energy 1 OAX: NOM Q2 2016 Presentation Oslo, 19 August 2016 Exploration and production of high-end minerals and metals 2 Nordic

256 views • 25 slides

Staff Recognition Pin Presentation October 6, 2017 NOTE: Ruth Ann Furgala, Board Chair;

Staff Recognition Pin Presentation October 6, 2017 NOTE: Ruth Ann Furgala, Board Chair; Krista Borgfjord, ETA President; and Cara Desimpelaere, CUPE Local President appear in all pictures but are only listed in the first one. 5 Year Pins

239 views • 4 slides

Weak Turbulence Theory for Reactive Instabilities Peter H. Yoon 1 Kinetic instabilities Im

Laboratory Space and Astrophysical Plasmas Pohang, Korea, June, 2008 Weak Turbulence Theory for Reactive Instabilities Peter H. Yoon 1 Kinetic instabilities Im ( , k ) Re ( , k ) = 0 , = Re ( , k ) /

196 views • 17 slides

R. Gary Hicks and Todd Shields TSP2 Emulsion Task Force Good materials specifications Good

R. Gary Hicks and Todd Shields TSP2 Emulsion Task Force Good materials specifications Good design practices Qualified personnel Contractor actually running the equipment Agency overseeing and accepting Solid Quality

520 views • 17 slides

Guide to Rates of Application of Primer Primer Pavement Grade Rate (L/m ) Tightly bonded

Design of Rates of Application Primes Primerseals Seals C170 binder Polymer modified binder Sprayed Seal Design Geotexle reinforced seals (GRS) AAPA training

222 views • 9 slides

Mobile App Development Frameworks Nader Boushehrinejadmoradi, Vinod Ganapathy, Santosh

Testing Cross-Platform Mobile App Development Frameworks Nader Boushehrinejadmoradi, Vinod Ganapathy, Santosh Nagarakatte, Liviu Iftode Department of Computer Science, Rutgers University ASE 2015 The Growing App Market A steady growth on

389 views • 28 slides