The Flying Monkey: a Mesoscale Robot that can Run, Fly, and Grasp

The agility and ease of control make a quadrotor aircraft an attractive platform for studying swarm behavior, modeling, and control. The energetics of sustained flight for small aircraft, however, limit typical applications to only a few minutes. Adding payloads – and the mechanisms used to manipulate them – reduces this flight time even further. 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 30 g 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 roots.National Science Foundation (U.S.) (IIS-1138847)National Science Foundation (U.S.) (EFRI-124038)National Science Foundation (U.S.) (CCF-1138967)United States. Army Research Laboratory (W911NF-08-2-0004)Wyss Institute for Biologically Inspired Engineerin

Small, Safe Quadrotors For Autonomous Flight

Autonomous flight through unknown environments in the presence of obstacles is a challenging problem for micro aerial vehicles (MAVs). A majority of the current state-of-art research focuses on modeling obstacles as opaque objects that can be easily sensed by optical sensors such as cameras or LiDARs. Since obstacles may not always be opaque, particularly in indoor environments with glass walls and windows, robots (like birds) have a difficult time navigating to the unknown environments. In this thesis, we describe the design, modeling, control and sensing for a new class of micro aerial vehicles that can navigate unknown environments and are robust to collisions. In particular, we present the design of the Tiercel MAV: a small, agile, light weight, collision-resistant robot powered by a cellphone grade CPU. The Tiercel is able to localize using a visual-inertial odometry (VIO) algorithm running on board the robot with a single downward-facing wide angle camera. Next, we characterize the effects of impacts and collisions on the visual-inertial odometry running on board the robot. We further develop the system architecture and components to enable the Tiercel to fly autonomously in an unknown space, detect collisions using its on board sensors, and leverage that information to build a 2-D map of the environment. Finally, we demonstrate the capability of a group of three Tiercel robots to navigate autonomously through an unknown, obstacle-ridden space while sustaining collisions with the environment. Finally, our approach exploits contact to infer the presence of transparent or reflective obstacles like glass walls, allowing us to naturally integrate touch with visual perception for exploration and mapping

Small, Safe Quadrotors for Autonomous Flight

Autonomous flight through unknown environments in the presence of obstacles is a challenging problem for micro aerial vehicles (MAVs). A majority of the current state-of-art research focuses on modeling obstacles as opaque objects that can be easily sensed by optical sensors such as cameras or LiDARs. Since obstacles may not always be opaque, particularly in indoor environments with glass walls and windows, robots (like birds) have a difficult time navigating to the unknown environments. In this thesis, we describe the design, modeling, control and sensing for a new class of micro aerial vehicles that can navigate unknown environments and are robust to collisions. In particular, we present the design of the Tiercel MAV: a small, agile, light weight, collision-resistant robot powered by a cellphone grade CPU. The Tiercel is able to localize using a visual-inertial odometry (VIO) algorithm running on board the robot with a single downward-facing wide angle camera. Next, we characterize the effects of impacts and collisions on the visual-inertial odometry running on board the robot. We further develop the system architecture and components to enable the Tiercel to fly autonomously in an unknown space, detect collisions using its on board sensors, and leverage that information to build a 2-D map of the environment. Finally, we demonstrate the capability of a group of three Tiercel robots to navigate autonomously through an unknown, obstacle-ridden space while sustaining collisions with the environment. Finally, our approach exploits contact to infer the presence of transparent or reflective obstacles like glass walls, allowing us to naturally integrate touch with visual perception for exploration and mapping

Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft MAV

We present a modular and extensible approach to integrate noisy measurements from multiple heterogeneous sensors that yield either absolute or relative observations at different and varying time intervals, and to provide smooth and globally consistent estimates of position in real time for autonomous flight. We describe the development of algorithms and software architecture for a new 1.9kg MAV platform equipped with an IMU, laser scanner, stereo cameras, pressure altimeter, magnetometer, and a GPS receiver, in which the state estimation and control are performed onboard on an Intel NUC 3rd generation i3 processor. We illustrate the robustness of our framework in large-scale, indoor-outdoor autonomous aerial navigation experiments involving traversals of over 440 meters at average speeds of 1.5 m/s with winds around 10 mph while entering and exiting buildings

A Modular Folded Laminate Robot Capable of Multi Modal Locomotion

This paper describes fundamental principles for two-dimensional pattern design of folded robots, specifically mobile robots consisting of closed-loop kinematic linkage mechanisms. Three fundamental methods for designing closed-chain folded four-bar linkages – the basic building block of these devices – are introduced. Modular connection strategies are also introduced as a method to overcome the challenges of designing assemblies of linkages from a two-dimensional sheet. The result is a design process that explores the tradeoffs between the complexity of linkage fabrication and also allows the designer combine multiple functions or modes of locomotion. A redesigned modular robot capable of multi-modal locomotion and grasping is presented to embody these design principles.National Science Foundation (Grants EFRI-1240383 and CCF- 1138967