Differences

This shows you the differences between two versions of the page.

--- ugv-uav_ab [2017/04/21 08:33] – blakehament
+++ ugv-uav_ab [2017/05/04 14:10] (current) – [7. Multi-rotor drone tutorial: systems, mechanics, control and state estimation] blakehament
@@ Line 18: / Line 18: @@
 ==== 1. Air-Ground Localization and Map Augmentation Using Monocular Dense Reconstruction ====
-[[rpg.ifi.uzh.ch/docs/IROS13_Forster_air-ground.pdf|Air-Ground Localization and Map Augmentation Using Monocular Dense Reconstruction]]\\
+[[http://ieeexplore.ieee.org/document/6696924/|Air-Ground Localization and Map Augmentation Using Monocular Dense Reconstruction]]\\
 Publisher: IROS 2013\\
@@ Line 209: / Line 209: @@
   - The key problem w/ UGV-UAV cooperation is data registration and fusion
   - Time constraints are salient in designing the algo's
-  - Use prior knowledge like motion projections and geometric properties to improve data fusion //
+  - Use prior knowledge like motion projections and geometric properties to improve data fusion \\
 **Blake liked this paper because:**
@@ Line 231: / Line 231: @@
-**[[ieeexplore.ieee.org/iel7/7478842/7487087/07487146.pdf|PLANNING FOR A GROUND-AIR ROBOTIC SYSTEM WITH COLLABORATIVE LOCALIZATION]]**\\
+**[[http://ieeexplore.ieee.org/document/7487146/|PLANNING FOR A GROUND-AIR ROBOTIC SYSTEM WITH COLLABORATIVE LOCALIZATION]]**\\
 Publisher: ICRA 2016\\
 Keywords (platform, field of research, algorithm or approach/methodologies, more details ): autonomous aerial vehicles;PAD planner;SLC planner;UGV-UAV team operating indoors;collaborative localization;controller-based motion primitives;ground-air robotic system;high-quality localization information;payload capacity;planning adaptive dimensionality;robust navigation capabilities;state lattice planner;unmanned aerial vehicles;unmanned ground vehicles;visual features;Collaboration;Lattices;Planning;Robot sensing systems;Trajectory \\
@@ Line 247: / Line 247: @@
+**This paper describes:** A state lattice planner using controller-based motion primitives (SLC) that uses planning with adaptive dimensionality (PAD)
+\\
+**The authors present (simulations, experiments, theory):** experiments using a state lattice planner using controller-based motion primitives (SLC) that uses planning with adaptive dimensionality (PAD)
+ \\
+**From this presentation, the paper concludes
+that:** success rates and trial stats showing the SLC PAD approach has a high rate of success and quick processing times\\
+**From the state-of-the-art, the paper identifies challenges in:** real-time planning for heterogeneous robot teams in which the robots do not need to travel in formation
+\\
+**The paper addresses these challenges by:** This paper proposes PAD such that only the relevant dimensions at a given point are considered. Ex: When moving a piano inside from the street, planning orientation is irrelevant in the drive-way but essential once you get to the doorway.
+\\
+**The results of this approach are:** superior success rates and times vs. existing methods \\
+**The paper presents the following theoretical principles:**
+  - State Lattice Controller (SLC)
+  - Motion Primitives
+  - Planning with Adaptive Dimensionality (PAD)
+\\
+**The principles are explained (choose: well/fairly/poorly):** fairly \\
+**For example (fill-in-the-blank e.g. the equations, graphs, figures),:** Table 1 **show the (choose: correct/questionable) application of the principles:** correct, but many of the figures are not very educational or interesting \\
+**From the principles and results, the paper concludes:**
+  - Existing methods of localization for UGV-UAV teams are lacking because of slow processing times and poor assumptions made by planners
+  - PAD allows for much faster processing times
+\\
+**Blake liked this paper because:** (fill-in-the-blank with at least 3 reasons if possible).\\
+**I disliked this paper because:** the authors didn't provide a toolkit with their algo's ;)  \\
+**I would have liked to see** the same work done without assuming any prior knowledge of the map \\
+**Three things I learned from this paper were:** \\
+  - state-based planning
+  - planning with adaptive dimensionality
+  - controlling with motion primitives
+**Time reading and annotating:** ~ 2 hours
+---
+\\
+==== 5. A Tutorial on Visual Servo Control ====
+**[[http://www.cs.jhu.edu/~hager/Public/Publications/TutorialTRA96.pdf|A Tutorial on Visual Servo Control]]**\\
+**Publisher:** ITRA 1996 \\
+**Keywords (platform, field of research, algorithm or approach/methodologies, more details ):** Jacobian matrices;correlation methods;feature extraction;feedback;image representation;motion control;optical tracking;robot dynamics;robot vision;servomechanisms;computer vision;coordinate transformations;correlation-based methods;feedback;image Jacobian;image feature tracking;image formation process;image-based systems;position-based system;robotic manipulators;tutorial;velocity representation;visual servo control;Control systems;Costs;Manipulators;Manufacturing;Robot control;Robot sensing systems;Robot vision systems;Servosystems;Tutorial;Visual servoing \\
+**Bibtex:**\\
+@ARTICLE{538972,
+author={S. Hutchinson and G. D. Hager and P. I. Corke},
+journal={IEEE Transactions on Robotics and Automation},
+title={A tutorial on visual servo control},
+year={1996},
+volume={12},
+number={5},
+pages={651-670},
+keywords={Jacobian matrices;correlation methods;feature extraction;feedback;image representation;motion control;optical tracking;robot dynamics;robot vision;servomechanisms;computer vision;coordinate transformations;correlation-based methods;feedback;image Jacobian;image feature tracking;image formation process;image-based systems;position-based system;robotic manipulators;tutorial;velocity representation;visual servo control;Control systems;Costs;Manipulators;Manufacturing;Robot control;Robot sensing systems;Robot vision systems;Servosystems;Tutorial;Visual servoing},
+doi={10.1109/70.538972},
+ISSN={1042-296X},
+month={Oct},}
+\\
+**This paper describes:** A taxonomy of and instructions for visual servoing (VS)\\
+**The authors present (simulations, experiments, theory):** A text tutorial containing the equations that govern the various approaches to VS\\
+**From this presentation, the paper concludes
+that:** A disclaimer that the paper presents a fundamental introduction, and readers should follow up with cited papers relevant to the VS they seek to implement.\\
+**From the state-of-the-art, the paper identifies challenges in:** processing times and environments with low visibility\\
+**The paper addresses these challenges by:** image-based rather than position-based VS; better camera positioning\\
+**The results of this approach are:** referenced in the 80+ citations in which they were implemented\\
+**The paper presents the following theoretical principles:**
+  - End point open vs. closed loop control
+  - Position vs. image based control
+  - Dynamic look-and-move vs. direct visual servo
+\\
+**The principles are explained (choose: well/fairly/poorly):** well \\
+**For example (fill-in-the-blank e.g. the equations, graphs, figures),:** Figs 3-6 **show the (choose: correct/questionable) application of the principles:** correct and very clear comparison of various VS architectures \\
+**From the principles and results, the paper concludes:**
+  - If the system is tracking movement of a target with known movement in cartesian coordinates, position-based tracking makes sense
+  - Otherwise, image-based tracking works better because it can be done independently of errors in robot kinematics or camera calibration
+\\
+**Blake liked this paper because:**
+  - It described relevant image convolution techniques
+  - It gave a concise but broad overview of the VS field
+  - It helped me refine the VS architecture most suited to UGV-UAV docking
+\\
+**I disliked this paper because:** I had to stop very frequently to look up computer vision or controls vocabulary; \\
+**I would have liked to see** more intermediary steps articulated \\
+**Three things I learned from this paper were:** \\
+  - Taxonomy of VS methods
+  - Several specific image matrix operations that are essential to VS
+  - Image-based VS tends to be more accurate, especially for the types of applications I will be implementing
+\\
+**Time reading and annotating:** ~ 5 hours
+---
+\\
+==== 6. A visual servoing docking approach for marsupial robotic system====
+**[[http://ieeexplore.ieee.org.ezproxy.library.unlv.edu/document/6896395/|A visual servoing docking approach for marsupial robotic system]]**\\
+**Publisher:** IEEE 2014 \\
+**Keywords (platform, field of research, algorithm or approach/methodologies, more details ):** cameras;feedback;mobile robots;multi-robot systems;robot vision;virtual machines;visual servoing;adistance state;aiming state;angular camera;around state;atangent state;blind state;child robot;decision-making unit;docking heading orientation;docking motion guide;image feature feedback;image-infor virtual machine;marsupial robotic system;parking state;pose refresher;rotational DOF;simulation platform design;task modelling;transform conditions;vertical V-shaped visual benchmark design;visual servoing docking approach;Benchmark testing;Cameras;Decision making;Robot kinematics;Robot vision systems;Virtual machining;Marsupial Robotic system;docking;image-infor virtual machine;visual servoing \\
+**Bibtex:**\\
+@INPROCEEDINGS{6896395,
+author={P. Zhao and Z. Cao and L. Xu and C. Zhou and D. Xu},
+booktitle={Proceedings of the 33rd Chinese Control Conference},
+title={A visual servoing docking approach for marsupial robotic system},
+year={2014},
+pages={8321-8325},
+keywords={cameras;feedback;mobile robots;multi-robot systems;robot vision;virtual machines;visual servoing;adistance state;aiming state;angular camera;around state;atangent state;blind state;child robot;decision-making unit;docking heading orientation;docking motion guide;image feature feedback;image-infor virtual machine;marsupial robotic system;parking state;pose refresher;rotational DOF;simulation platform design;task modelling;transform conditions;vertical V-shaped visual benchmark design;visual servoing docking approach;Benchmark testing;Cameras;Decision making;Robot kinematics;Robot vision systems;Virtual machining;Marsupial Robotic system;docking;image-infor virtual machine;visual servoing},
+doi={10.1109/ChiCC.2014.6896395},
+month={July},}
+\\
+**This paper describes:** A docking method for a child robot loading into a compartment in a mother robot\\
+**The authors present (simulations, experiments, theory):** task model for docking, algo, and simulated results \\
+**From this presentation, the paper concludes
+that:** the simulated results confirm the validity of the docking approach and it's anti-interrupt ability\\
+**From the state-of-the-art, the paper identifies challenges in:** Controls for and implementation of marsupial robots\\
+**The paper addresses these challenges by:** applying standard color and geometry triggered VS controls to docking of marsupial robots\\
+**The results of this approach are:** Quick docking times, robust performance even with unexpected perturbations in the robots motion/rotation from the researchers\\
+**The paper presents the following theoretical principles:**
+  - Marsupial robotics
+  - Visual Servoing
+  - Decision-making in Different States
+\\
+**The principles are explained (choose: well/fairly/poorly):** well \\
+**For example (fill-in-the-blank e.g. the equations, graphs, figures),:** Fig. 4 **show the (choose: correct/questionable) application of the principles:**correct application of the decision-making algo \\
+**From the principles and results, the paper concludes:**
+  - Future work will focus on retrieval of child robots
+\\
+**Blake liked this paper because:**
+  - Almost identical VS docking strategy to my method for UGV docking in a box suspended from a UAV
+  - They showed their rotation and transformation matrices which will be a good check for my future work if I pursue the box method
+\\
+**I disliked this paper because:** Although I am happy for the walkthrough of their project as I might compare my results at various stages, I am not sure they pushed any borders of knowledge ; \\
+**I would have liked to see** More discussion of the simulation \\
+**Three things I learned from this paper were:** \\
+  - Vocabulary for the stages in docking
+  - "V" approach to docking with VS
+  - Pose refreshment in simulation-- could apply similar equations to VR
+\\
+**Time reading and annotating:** ~ 15 min
+---
+\\
+==== 7. Multi-rotor drone tutorial: systems, mechanics, control and state estimation ====
+**[[https://link.springer.com/article/10.1007/s11370-017-0224-y|Multi-rotor drone tutorial: systems, mechanics, control and state estimation]]**\\
+**Publisher:** Intelligent Service Robotics 2017 \\
+**Keywords (platform, field of research, algorithm or approach/methodologies, more details ):** Components · Control · Modeling · Multi-rotor drone · Sensor fusion \\
+**Bibtex:**\\
+@Article{Yang2017,
+author="Yang, Hyunsoo
+and Lee, Yongseok
+and Jeon, Sang-Yun
+and Lee, Dongjun",
+title="Multi-rotor drone tutorial: systems, mechanics, control and state estimation",
+journal="Intelligent Service Robotics",
+year="2017",
+volume="10",
+number="2",
+pages="79--93",
+issn="1861-2784",
+doi="10.1007/s11370-017-0224-y",
+url="http://dx.doi.org/10.1007/s11370-017-0224-y"
+}
+\\
 **This paper describes:** \\
@@ Line 262: / Line 475: @@
-**The paper presents the following theoretical principles:** (1) (fill-in-the-blank);
+**The paper presents the following theoretical principles:**
-(2) (fill-in-the-blank);.... ; and (n) (fill-in-the-blank).
+  - Ordered List Item
+  -
-**The principles are explained (choose: well/fairly/poorly):** fairly \\
+\\
+**The principles are explained (choose: well/fairly/poorly):**  \\
 **For example (fill-in-the-blank e.g. the equations, graphs, figures),:**  **show the (choose: correct/questionable) application of the principles:** \\
-**From the principles and results, the paper concludes:** (fill-in-the-blank);
+**From the principles and results, the paper concludes:**
-(2) (fill-in-the-blank);.... ; and (n) (fill-in-the-blank).
+  -
+\\
-**Blake liked this paper because:** (fill-in-the-blank with at least 3 reasons if possible).\\
+**Blake liked this paper because:**
+  - 1
-**I disliked this paper because:** (fill-in-the-blank); \\
+  - 2
-**I would have liked to see** (fill-in-the-blank). \\
+  - 3
+\\
+**I disliked this paper because:** ; \\
+**I would have liked to see**  \\
 **Three things I learned from this paper were:** \\
-(1) (fill-in-the-blank); \\
+  - 1
-(2) (fill-in-the-blank); \\
+  - 2
-and (3) (fill-in-the-blank).\\
+  - 3
-**Time reading and annotating:** ~ 1.5 hours
+\\
+**Time reading and annotating:** ~  hours
 ---
+\\
+---
+\\
+==== . ====
-**3.[[rpg.ifi.uzh.ch/docs/IROS13_Forster_air-ground.pdf|LOCALIZATION, MAPPING, MONOCULAR DENSE RECONSTRUCTION]]**\\
-Publisher: IROS 2013\\
-Keywords (platform, field of research, algorithm or approach/methodologies, more details ): image reconstruction;mobile robots;position measurement;robot vision;3D map registration;3D reconstruction;MAV monocular camera;Monte Carlo localization;air-ground localization;depth sensor;ground robot;iterative pose refinement;live dense reconstruction;map augmentation;micro aerial vehicle;monocular dense reconstruction;position estimation;sensors;vantage points;visual feature matching;Cameras;Robot kinematics;Simultaneous localization and mapping;Three-dimensional displays \\
-**
-Bibtex:**\\
-@INPROCEEDINGS{6696924,
+**[[|]]**\\
-author={C. Forster and M. Pizzoli and D. Scaramuzza},
+**Publisher:** \\
-booktitle={2013 IEEE/RSJ International Conference on Intelligent Robots and Systems},
+**Keywords (platform, field of research, algorithm or approach/methodologies, more details ):**  \\
-title={Air-ground localization and map augmentation using monocular dense reconstruction},
+**Bibtex:**\\
-year={2013},
-pages={3971-3978},
-keywords={image reconstruction;mobile robots;position measurement;robot vision;3D map registration;3D reconstruction;MAV monocular camera;Monte Carlo localization;air-ground localization;depth sensor;ground robot;iterative pose refinement;live dense reconstruction;map augmentation;micro aerial vehicle;monocular dense reconstruction;position estimation;sensors;vantage points;visual feature matching;Cameras;Robot kinematics;Simultaneous localization and mapping;Three-dimensional displays},
-doi={10.1109/IROS.2013.6696924},
-ISSN={2153-0858},
-month={Nov},}
+\\
 **This paper describes:** \\
@@ Line 320: / Line 535: @@
-**The paper presents the following theoretical principles:** (1) (fill-in-the-blank);
+**The paper presents the following theoretical principles:**
-(2) (fill-in-the-blank);.... ; and (n) (fill-in-the-blank).
+  - Ordered List Item
+  -
+\\
+**The principles are explained (choose: well/fairly/poorly):**  \\
-**The principles are explained (choose: well/fairly/poorly):** fairly \\
+**For example (fill-in-the-blank e.g. the equations, graphs, figures),:**  **show the (choose: correct/questionable) application of the principles:** \\
+**From the principles and results, the paper concludes:**
+  -
+\\
+**Blake liked this paper because:**
+  - 1
+  - 2
+  - 3
+\\
+**I disliked this paper because:** ; \\
+**I would have liked to see**  \\
+**Three things I learned from this paper were:** \\
+  - 1
+  - 2
+  - 3
+\\
+**Time reading and annotating:** ~  hours
+---
+\\
+---
+\\
+==== . ====
+**[[|]]**\\
+**Publisher:** \\
+**Keywords (platform, field of research, algorithm or approach/methodologies, more details ):**  \\
+**Bibtex:**\\
+\\
+**This paper describes:** \\
+**The authors present (simulations, experiments, theory):** \\
+**From this presentation, the paper concludes
+that:** \\
+**From the state-of-the-art, the paper identifies challenges in:** \\
+**The paper addresses these challenges by:** \\
+**The results of this approach are:** \\
+**The paper presents the following theoretical principles:**
+  - Ordered List Item
+  -
+\\
+**The principles are explained (choose: well/fairly/poorly):**  \\
 **For example (fill-in-the-blank e.g. the equations, graphs, figures),:**  **show the (choose: correct/questionable) application of the principles:** \\
-**From the principles and results, the paper concludes:** (fill-in-the-blank);
+**From the principles and results, the paper concludes:**
-(2) (fill-in-the-blank);.... ; and (n) (fill-in-the-blank).
+  -
+\\
-**Blake liked this paper because:** (fill-in-the-blank with at least 3 reasons if possible).\\
+**Blake liked this paper because:**
+  - 1
+  - 2
+  - 3
+\\
+**I disliked this paper because:** ; \\
+**I would have liked to see**  \\
-**I disliked this paper because:** (fill-in-the-blank); \\
+**Three things I learned from this paper were:** \\
-**I would have liked to see** (fill-in-the-blank). \\
+  - 1
+  - 2
+  - 3
+\\
+**Time reading and annotating:** ~  hours
+---
+==== . ====
+**[[|]]**\\
+**Publisher:** \\
+**Keywords (platform, field of research, algorithm or approach/methodologies, more details ):**  \\
+**Bibtex:**\\
+\\
+**This paper describes:** \\
+**The authors present (simulations, experiments, theory):** \\
+**From this presentation, the paper concludes
+that:** \\
+**From the state-of-the-art, the paper identifies challenges in:** \\
+**The paper addresses these challenges by:** \\
+**The results of this approach are:** \\
+**The paper presents the following theoretical principles:**
+  - Ordered List Item
+  -
+\\
+**The principles are explained (choose: well/fairly/poorly):**  \\
+**For example (fill-in-the-blank e.g. the equations, graphs, figures),:**  **show the (choose: correct/questionable) application of the principles:** \\
+**From the principles and results, the paper concludes:**
+  -
+\\
+**Blake liked this paper because:**
+  - 1
+  - 2
+  - 3
+\\
+**I disliked this paper because:** ; \\
+**I would have liked to see**  \\
 **Three things I learned from this paper were:** \\
-(1) (fill-in-the-blank); \\
+  - 1
-(2) (fill-in-the-blank); \\
+  - 2
-and (3) (fill-in-the-blank).\\
+  - 3
-**Time reading and annotating:** ~ 1.5 hours
+\\
+**Time reading and annotating:** ~  hours
 ---
+\\
+---
+\\