Update CollisionConeCBF.md

Author: tayalmanan28

_projects/CollisionConeCBF.md

@@ -6,23 +6,38 @@ description: |
   
 people:
   - manan
-  - phani
   - bhavya
+  - phani
+  - shishir
 
 layout: project
 image: "/img/c3bf.png"
 last-updated: 2023-03-28
 ---
-### Introduction 
-In this paper, we propose a new class of Control Barrier Functions (CBFs) that helps avoid collisions with kinematic (nonzero velocity) obstacles. While the current forms of CBFs have been successful in guaranteeing safety/collision avoidance with static obstacles, extensions for the dynamic case with torque/acceleration-controlled unicycle and bicycle models have seen limited success. 
+## Introduction 
+This work presents a unified approach for collision avoidance using Collision-Cone Control Barrier Functions (CBFs) in both ground (UGV) and aerial (UAV) unmanned vehicles. We propose a novel CBF formulation inspired by collision cones, commonly used in trajectory planning, to ensure safety by constraining the relative velocity between the vehicle and the obstacle to always point away from each other. The efficacy of this approach is demonstrated through simulations and hardware implementations on the Turtlebot, Stoch-Jeep (Ackermann), and Crazyflie 2.1 quadrotor robot, showcasing its effectiveness in avoiding collisions with dynamic obstacles in both ground and aerial settings. The real-time controller is developed using CBF Quadratic Programs (QPs) formulation. Comparative analysis with existing CBF-QPs, particularly Higher-Order CBF (HOCBF), highlights the less conservative nature of the proposed approach. Overall, this research contributes to a novel control formation that can give a guarantee for collision avoidance in unmanned vehicles by modifying the control inputs from existing path-planning controllers, enhancing the vehicle's maneuverability and safety in dynamic environments.
+
+## Simulation Results
+### Obstacle avoidance on UGVs (Unicycle & Bicycle Models)
+<iframe width="560" height="315" src="https://www.youtube.com/embed/Dme7Wm9y6es?si=MJtqDGpFVl71ZDMD" 
+      title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
+
+### Obstacle avoidance on UAV (Quadrotor Model)
+<iframe width="560" height="315" src="https://www.youtube.com/embed/oTauuHCpFM0?si=xlMvqoxhGrRpvOgm" 
+      title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
 
-<!-- <br/>
-<img src="{{site.base}}/img/tile_backtrot.png" alt="drawing" width="600"/>
-<img src="{{site.base}}/img/tile_sidestep.png" alt="drawing" width="600"/>
-<img src="{{site.base}}/img/tile_turn.png" alt="drawing" width="600"/>
+## Hardware Experiments
+### Obstacle avoidance on Turlebot (Unicycle Model)
+<iframe width="560" height="315" src="https://www.youtube.com/embed/L7y6x_121T8?si=2Vf_1IINKDDmOGqv" 
+      title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
 
-[![Gait Library Synthesis](http://i3.ytimg.com/vi/3BQYX2vZdAg/hqdefault.jpg)](https://www.youtube.com/watch?v=3BQYX2vZdAg&t=97s&ab_channel=Stoch_IISc "GaitLibrary")
-[![Learning Stable Manuveuers](http://i3.ytimg.com/vi/LRbHetp0dcg/hqdefault.jpg)](https://www.youtube.com/watch?v=LRbHetp0dcg&t=15s&ab_channel=kartikpaigwar "ROMAN") -->
+### Obstacle avoidance on Stoch-Jeep (Bicycle Model)
+<iframe width="560" height="315" src="https://www.youtube.com/embed/bYME1ZF98TQ?si=5I-RhM3igN1eQD9-" 
+      title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
+
+### Obstacle avoidance on Crazyflie 2.1 (Quadrotor Model)</h3>
+<iframe width="560" height="315" src="https://www.youtube.com/embed/_OIX3QhtQUM?si=4oo1aWrbs3rv9hFT" 
+      title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
 
 <br/>
 ## Citation ##
@@ -40,6 +55,14 @@ In this paper, we propose a new class of Control Barrier Functions (CBFs) that h
           journal={arXiv preprint arXiv:2303.15871},
           year={2023}
         }
+        @misc{goswami2023collision,
+              title={Collision Cone Control Barrier Functions: Experimental Validation on UGVs for Kinematic Obstacle Avoidance}, 
+              author={Bhavya Giri Goswami and Manan Tayal and Karthik Rajgopal and Pushpak Jagtap and Shishir Kolathaya},
+              year={2023},
+              eprint={2310.10839},
+              archivePrefix={arXiv},
+              primaryClass={cs.RO}
+        }
         
 ```
-<br/>
+<br/>