233 citations · 2.4k across the 215 of their papers we have counts for
17 papers · 2 filters
TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions
Rohan Chandra, Uttaran Bhattacharya, Aniket Bera +1
We present a new algorithm for predicting the near-term trajectories of road-agents in dense traffic videos. Our approach is designed for heterogeneous traffic, where the road-agen…
Solving Chance Constrained Optimization under Non-Parametric Uncertainty Through Hilbert Space Embedding
Bharath Gopalakrishnan, Arun Kumar Singh, K. Madhava Krishna +1
In this paper, we present an efficient algorithm for solving a class of chance constrained optimization under non-parametric uncertainty. Our algorithm is built on the possibility…
Collision-Free Kinematics for Redundant Manipulators in Dynamic Scenes using Optimal Reciprocal Velocity Obstacles
Liangliang Zhao, Jingdong Zhao, Hong Liu +1
We present a novel algorithm for collision-free kinematics of multiple manipulators in a shared workspace with moving obstacles. Our optimization-based approach simultaneously hand…
Fast Motion Planning for High-DOF Robot Systems Using Hierarchical System Identification
Biao Jia, Zherong Pan, Dinesh Manocha
We present an efficient algorithm for motion planning and control of a robot system with a high number of degrees-of-freedom. These include high-DOF soft robots or an articulated r…
Pedestrian Dominance Modeling for Socially-Aware Robot Navigation
Tanmay Randhavane, Aniket Bera, Emily Kubin +3
We present a Pedestrian Dominance Model (PDM) to identify the dominance characteristics of pedestrians for robot navigation. Through a perception study on a simulated dataset of pe…
TZC: Efficient Inter-Process Communication for Robotics Middleware with Partial Serialization
Yu-Ping Wang, Wende Tan, Xu-Qiang Hu +2
Inter-process communication (IPC) is one of the core functions of modern robotics middleware. We propose an efficient IPC technique called TZC (Towards Zero-Copy). As a core compon…
Getting Robots Unfrozen and Unlost in Dense Pedestrian Crowds
Tingxiang Fan, Xinjing Cheng, Jia Pan +4
We aim to enable a mobile robot to navigate through environments with dense crowds, e.g., shopping malls, canteens, train stations, or airport terminals. In these challenging envir…
Diffraction-Aware Sound Localization for a Non-Line-of-Sight Source
Inkyu An, Doheon Lee, Jung-woo Choi +2
We present a novel sound localization algorithm for a non-line-of-sight (NLOS) sound source in indoor environments. Our approach exploits the diffraction properties of sound waves…
Safe Navigation with Human Instructions in Complex Scenes
Zhe Hu, Jia Pan, Tingxiang Fan +2
In this paper, we present a robotic navigation algorithm with natural language interfaces, which enables a robot to safely walk through a changing environment with moving persons b…
CrowdMove: Autonomous Mapless Navigation in Crowded Scenarios
Tingxiang Fan, Xinjing Cheng, Jia Pan +2
Navigation is an essential capability for mobile robots. In this paper, we propose a generalized yet effective 3M (i.e., multi-robot, multi-scenario, and multi-stage) training fram…
Transferring Grasp Configurations using Active Learning and Local Replanning
Hao Tian, Changbo Wang, Dinesh Manocha +1
We present a new approach to transfer grasp configurations from prior example objects to novel objects. We assume the novel and example objects have the same topology and similar s…
Learning-based Feedback Controller for Deformable Object Manipulation
Biao Jia, Zhe Hu, Zherong Pan +2
In this paper, we present a general learning-based framework to automatically visual-servo control the position and shape of a deformable object with unknown deformation parameters…
PORCA: Modeling and Planning for Autonomous Driving among Many Pedestrians
Yuanfu Luo, Panpan Cai, Aniket Bera +3
This paper presents a planning system for autonomous driving among many pedestrians. A key ingredient of our approach is PORCA, a pedestrian motion prediction model that accounts f…
The Socially Invisible Robot: Navigation in the Social World using Robot Entitativity
Aniket Bera, Tanmay Randhavane, Emily Kubin +3
We present a real-time, data-driven algorithm to enhance the social-invisibility of robots within crowds. Our approach is based on prior psychological research, which reveals that…
AutoRVO: Local Navigation with Dynamic Constraints in Dense Heterogeneous Traffic
Yuexin Ma, Dinesh Manocha, Wenping Wang
We present a novel algorithm for computing collision-free navigation for heterogeneous road-agents such as cars, tricycles, bicycles, and pedestrians in dense traffic. Our approach…
Identifying Driver Behaviors using Trajectory Features for Vehicle Navigation
Ernest Cheung, Aniket Bera, Emily Kubin +2
We present a novel approach to automatically identify driver behaviors from vehicle trajectories and use them for safe navigation of autonomous vehicles. We propose a novel set of…
Cloth Manipulation Using Random-Forest-Based Imitation Learning
Biao Jia, Zherong Pan, Zhe Hu +2
We present a novel approach for robust manipulation of high-DOF deformable objects such as cloth. Our approach uses a random forest-based controller that maps the observed visual f…