4 citations · 10 across the 12 of their papers we have counts for
16 papers
Towards Real-World Identification of Fatigued Muscle Groups via Musculoskeletal Simulation
Jenishkumar Chauhan, Samarth Brahmbhatt, Vineet Vashista
Contactless diagnosis of musculoskeletal disorders can potentially improve population health as well as robot behaviours in collaborative settings. However, current diagnosis metho…
Imagine2Servo: Intelligent Visual Servoing with Diffusion-Driven Goal Generation for Robotic Tasks
Pranjali Pathre, Gunjan Gupta, M. Nomaan Qureshi +3
Visual servoing, the method of controlling robot motion through feedback from visual sensors, has seen significant advancements with the integration of optical flow-based methods.…
OpenBot-Fleet: A System for Collective Learning with Real Robots
Matthias Müller, Samarth Brahmbhatt, Ankur Deka +3
We introduce OpenBot-Fleet, a comprehensive open-source cloud robotics system for navigation. OpenBot-Fleet uses smartphones for sensing, local compute and communication, Google Fi…
The Un-Kidnappable Robot: Acoustic Localization of Sneaking People
Mengyu Yang, Patrick Grady, Samarth Brahmbhatt +3
How easy is it to sneak up on a robot? We examine whether we can detect people using only the incidental sounds they produce as they move, even when they try to be quiet. We collec…
Zero-Shot Transfer of Haptics-Based Object Insertion Policies
Samarth Brahmbhatt, Ankur Deka, Andrew Spielberg +1
Humans naturally exploit haptic feedback during contact-rich tasks like loading a dishwasher or stocking a bookshelf. Current robotic systems focus on avoiding unexpected contact,…
Visual Pressure Estimation and Control for Soft Robotic Grippers
Patrick Grady, Jeremy A. Collins, Samarth Brahmbhatt +4
Soft robotic grippers facilitate contact-rich manipulation, including robust grasping of varied objects. Yet the beneficial compliance of a soft gripper also results in significant…
PressureVision: Estimating Hand Pressure from a Single RGB Image
Patrick Grady, Chengcheng Tang, Samarth Brahmbhatt +4
People often interact with their surroundings by applying pressure with their hands. While hand pressure can be measured by placing pressure sensors between the hand and the enviro…
ContactOpt: Optimizing Contact to Improve Grasps
Patrick Grady, Chengcheng Tang, Christopher D. Twigg +3
Physical contact between hands and objects plays a critical role in human grasps. We show that optimizing the pose of a hand to achieve expected contact with an object can improve…
ContactPose: A Dataset of Grasps with Object Contact and Hand Pose
Samarth Brahmbhatt, Chengcheng Tang, Christopher D. Twigg +2
Grasping is natural for humans. However, it involves complex hand configurations and soft tissue deformation that can result in complicated regions of contact between the hand and…
Towards Markerless Grasp Capture
Samarth Brahmbhatt, Charles C. Kemp, James Hays
Humans excel at grasping objects and manipulating them. Capturing human grasps is important for understanding grasping behavior and reconstructing it realistically in Virtual Reali…
ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
Samarth Brahmbhatt, Cusuh Ham, Charles C. Kemp +1
Grasping and manipulating objects is an important human skill. Since hand-object contact is fundamental to grasping, capturing it can lead to important insights. However, observing…
ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact
Samarth Brahmbhatt, Ankur Handa, James Hays +1
Grasping and manipulating objects is an important human skill. Since most objects are designed to be manipulated by human hands, anthropomorphic hands can enable richer human-robot…
Geometry-Aware Learning of Maps for Camera Localization
Samarth Brahmbhatt, Jinwei Gu, Kihwan Kim +2
Maps are a key component in image-based camera localization and visual SLAM systems: they are used to establish geometric constraints between images, correct drift in relative pose…
DeepNav: Learning to Navigate Large Cities
Samarth Brahmbhatt, James Hays
We present DeepNav, a Convolutional Neural Network (CNN) based algorithm for navigating large cities using locally visible street-view images. The DeepNav agent learns to reach its…
StuffNet: Using 'Stuff' to Improve Object Detection
Samarth Brahmbhatt, Henrik I. Christensen, James Hays
We propose a Convolutional Neural Network (CNN) based algorithm - StuffNet - for object detection. In addition to the standard convolutional features trained for region proposal an…
Occlusion-Aware Object Localization, Segmentation and Pose Estimation
Samarth Brahmbhatt, Heni Ben Amor, Henrik Christensen
We present a learning approach for localization and segmentation of objects in an image in a manner that is robust to partial occlusion. Our algorithm produces a bounding box aroun…