S5: Small, Safe, Smart, Speedy, Swarms of Aerial Robots

Abstract

During the last decade, small (0.1-0.5 m in length) and lightweight (0.1-0.5 kg) Unmanned Aerial Vehicles (UAVs), and ground vehicles (UGVs), began playing a major role in different humanitarian and surveillance tasks such as searchand rescue, disaster response, reconnaissance missions, inspection of critical areas and environment interactions.These settings require UAVs that can navigate complex, three-dimensional, indoor and outdoor environments andinteract with them.We need to develop the robust mathematical frameworks, new learning algorithms, and new hardware to provide fullautonomous capabilities for multi-robot teams of aerial and ground vehicles. In particular, our major interests are in thedevelopment of new robust decentralized localization and control algorithms, software tools, learning and environmentinteraction algorithms and new multi-platform hardware systems to achieve autonomous cooperative teams of aerialand ground vehicles. The vehicles have to reliably operate and coordinate in highly constrained, challenging anddynamic environments with lossy communications. Specifically, this proposal focuses on the 5 S~s of Aerial Robotics such as: (1) Size: smaller robots (2) Safe: safer operation around humans, animals and the environment (3) Smart: autonomous robots with onboard intelligence (4) Speed: faster more agile robots (5) Swarms: cooperation between robots.Our research will emphasize the previously mentioned topics focusing on small and lightweight platforms where, thesize, weight and payload constraints only allow lightweight sensors like cameras, and the operating conditions of highspeeds require inter-vehicle coordination, perception, state estimation, environment reconstruction, obstacle avoidanceand planning algorithms over longer ranges and shorter time scales. In these contexts, the perception, control,coordination and planning have to be studied as an unique problem.The proposed research leverages multiple research results from previous DoD projects as well as ongoing projects,that will provide support for graduate students and postdoctoral fellows.

Document Details

Document Type
DoD Grant Award
Publication Date
May 05, 2017
Source ID
N000141712437

Entities

People

  • R.vijay Kumar

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Pennsylvania

Tags

Fields of Study

  • Computer science

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Distributed Systems and Data Platform Development
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - UAVs