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Published on Sep 11, 2016
This video presents an autonomous 250 g quadrotor performing aggressive maneuvers using a qualcomm snapdragon flight and relying only on on-board computation and sensor capabilities. The control planning and estimation tasks are solved based on the information provided by a single camera and an IMU.
Highlights from DARPA’s Fast Light Autonomy competition data collection tests. The fastest flight was from Penn’s “Team Falcon” from the GRASP Lab! Other teams composed of MIT/Draper and SSCI/AV.
In this paper we present the flying monkey, a novel robot platform having three main capabilities: walking, grasping, and flight. This new robotic platform merges one of the world’s smallest quadrotor aircraft with a lightweight, single-degree-of-freedom walking mechanism and an SMA-actuated gripper to enable all three functions in a 30g package. The main goal and key contribution of this paper is to design and prototype the flying monkey that has increased mission life and capabilities through the combination of the functionalities of legged and aerial robots. Yash Mulgaonkar, Brandon Araki, Je-sung Koh, Luis Guerrero-Bonilla, Daniel M. Aukes, Anurag Makineni, Michael T. Tolley, Daniela Rus, Robert J. Wood, and Vijay Kumar.
Sikang Liu, Michael Watterson, Sarah Tang, and Vijay Kumar
Justin Thomas, Giuseppe Loianno, Morgan Pope, Elliot W. Hawkes, Matthew A. Estrada, Hao Jiang, Mark R. Cutkosky, Vijay Kumar.
This video showcases a research collaboration between our group at the University of Pennsylvania and Qualcomm Research in creating autonomous flying robots powered by smartphones. The (750 g, 54 cm diameter) robot is designed and build at Penn. The sensing, sensor fusion, control, and planning are all done on an off-the-shelf Samsung Galaxy S5 phone. The robot senses its environment and estimates its pose using information from the camera and IMU on the phone.
Quadrotor flying along the horizontal region of the penstock without external illumination. We collect imagery using the on-board camera and use visual odometry to estimate position along the tunnel axis.
Quadrotor flying along the inclined region of the penstock approximately 50 meters into the inclination. We collect imagery using the on-board camera and use visual odometry to estimate position along the tunnel axis.
Quadrotor flying along the inclined region of the penstock approximately 15 meters into the inclination. We collect imagery using the on-board camera and use visual odometry to estimate position along the tunnel axis.
Scalable sWarms of Autonomous Robots and Mobile Sensors (SWARMS) project.
The SWARMS project brings together experts in artificial intelligence, control theory, robotics, systems engineering and biology with the goal of understanding swarming behaviors in nature and applications of biologically-inspired models of swarm behaviors to large networked groups of autonomous vehicles.
This video accompanies our submission to ICRA 2019 on multi-MAV mutual localization under the following assumptions:
1. Initial relative poses between robots are unknown.
2. Robot detection provides no identity information.
3. Item Robot detection can include false negatives and false positives.
4. Vision-based distance and bearing measurements are noisy.
Aerial Robots for Remote Autonomous Exploration and Mapping
We are interested in exploring the possibility of leveraging an autonomous quadrotor in earthquake-damaged environments through field experiments that focus on cooperative mapping using both ground and aerial robots. Aerial robots offer several advantages over ground robots, including the ability to maneuver through complex three-dimensional (3D) environments and gather data from vantages inaccessible to ground robots. Read More …
N. Michael, S. Shen, K. Mohta, Y. Mulgaonkar, V. Kumar, K. Nagatani, Y. Okada, S. Kiribayashi, K. Otake, K. Yoshida, K. Ohno, E. Takeuchi, and S. Tadokoro, “Collaborative mapping of an earthquake-damaged building via ground and aerial robots,” J. Field Robotics, vol. 29, no. 5, pp. 832–841, 2012.
CPS: Frontier: Collaborative Research: bioCPS for Engineering Living Cells
Calin Belta-Boston University (Lead PI)
Doug Densmore-Boston University (Co-PI)
Vijay Kumar- University of Pennsylvania (PI)
Ron Weiss- Massachusetts Institute of Technology (PI)
We combine strategies for passive particle assembly in soft matter with robotics to develop new means of controlled interaction. In capillary assembly, particles distort fluid interfaces and move in directions that minimize the surface area. In particular, they move along principle axes on curved interfaces to sites of high curvature via capillary migration. We propose a robot that serves as a programmable source of fluid curvature and allows the collection of passive particles. When settled on a fluid interface, the magnetic robot distorts the interface, which strongly influences curvature capillary migration. The shape of the robot dictates the interface shape, for example, by imposing high interface curvature near corners, create sites of preferred assembly. This freedom to manipulate interface curvature dynamically and to migrate laterally on the interface creates new possibilities for directed bottom-up particle assemblies and precise manipulation of these complex assembled structures. Since the passive particles can be functionalized to sense, report and interact with their surroundings, this work paves the way to new schemes for creation and control of functionalized micro robots.
Independent Control of Identical Magnetic Robots in Plane
Denise Wong, Edward Steager, Vijay Kumar