Jean-Christophe Zufferey

Fly-inspired visual steering of an ultralight indoor aircraft

We aim at developing autonomous microflyers capable of navigating within houses or small indoor environments using vision as the principal source of information. Due to severe weight and energy constraints, inspiration is taken from the fly for the selection of sensors, for signal processing, and for the control strategy. The current 30-g prototype is capable of autonomous steering in a 16/spl times/16 m textured environment. This paper describes models and algorithms which allow for efficient course stabilization and collision avoidance using optic flow and inertial information.

A miniature 7g jumping robot

Jumping can be a very efficient mode of locomotion for small robots to overcome large obstacles and travel in natural, rough terrain. In this paper we present the development and characterization of a novel 5 cm, 7g jumping robot. It can jump obstacles more than 27 times its own size and outperforms existing jumping robots by one order of magnitude with respect to jump height per weight and jump height per size. It employs elastic elements in a four bar linkage leg system to allow for very powerful jumps and adjustment of the jumping force, take-off angle and force profile during the acceleration phase.

Energy management for indoor hovering robots

Flying has an advantage when compared to ground based locomotion, as it simplifies the task of overcoming obstacles and allows for rapid coverage of an area while also providing a birds-eye-view of the environment. One of the key challenges that has prevented engineers from coming up with convincing aerial solutions for indoor exploration is the energetic cost of flying. This paper presents a way of mitigating the energy problem regarding aerial exploration within indoor environments. This is achieved by means of a model to estimate the endurance of a hover-capable flying robot and by using ceiling attachment as a means of preserving energy while maintaining a birds-eye-view. The proposed model for endurance estimation has been extensively tested using a custom-developed quadrotor and autonomous ceiling attachment system.

Autonomous flight at low altitude using light sensors and little computational power

The ability to fly at low altitude while actively avoiding collisions with the terrain and objects such as trees and buildings is a great challenge for small unmanned aircraft. This paper builds on top of a control strategy called optiPilot whereby a series of optic-flow detectors pointed at divergent viewing directions around the aircraft main axis are linearly combined into roll and pitch commands using two sets of weights. This control strategy already proved successful at controlling flight and avoiding collisions in reactive navigation experiments. This paper describes how optiPilot can efficiently steer a flying platform during the critical phases of hand-launched take off and landing. It then shows how optiPilot can be coupled with a GPS in order to provide goal-directed, nap-of-the-earth flight control in presence of obstacles. Two fully autonomous flights of 25 minutes each are described where a 400-gram unmanned aircraft flies at approx. 10 m above ground in a circular path including two copses of trees requiring efficient collision avoidance actions.

Implementation of a wireless mesh network of ultra light MAVs with dynamic routing

This paper describes the implementation and characterisation of a mobile ad-hoc network (MANET) of ultra-light intelligent flying robots. The flying nature of the network makes it suitable to collect or disseminate content in urban areas or challenging terrain, where line-of-sight connection between the Micro Air Vehicles (MAVs) allows for more efficient communication. Dynamic routing in the network enables the nodes to intelligently establish multi-hop routes to extend the communication range or to overcome obstacles. The presented MANET relies on the IEEE 802.11n WiFi standard for data communications and uses the OLSR routing protocol. Routing decisions based on dynamic link quality measurements allow the network to cope with the fast variability of the wireless channel and the high mobility of the MAVs. The implementation of such a system calls for the integration of advanced communication and control technologies in a very restrictive platform, be it in terms of weight, power consumption or availability of suitable off-the-shelf hardware. A detailed description of the system design is presented, and its performance is characterised based on in-flight network measurements. To the best of our knowledge, this is the first report of OLSR successfully tested in a MANET with such fast dynamics. We verify the trade-off between achievable throughput and the number of hops, and we report on the sensitivity of communication performance and routing behaviour to MAV orientation and flight path. Mitigation of such dependencies and improvements to the routing algorithm are discussed along with future research directions.

Vision-based altitude and pitch estimation for ultra-light indoor microflyers

Autonomous control of ultra-light indoor microflyers is a difficult and largely unsolved task because of the strong limitations on the kind of sensors that can be embedded. We propose a new approach for altitude control of a 10-gram microflyer, where altitude as well as pitch angle are estimated using a set of visual, airspeed and gyroscopic sensors that weight about 1 (g) in total. This approach does not rely on an explicit estimation of optic flow, but rather takes as input the raw images as provided by the vision sensor. We show that altitude and pitch angle of a simulated agent can be successfully estimated. This result is thus a first step toward autonomous altitude control of indoor flying robots

An Active Uprighting Mechanism for Flying Robots

Flying robots have unique advantages in the exploration of cluttered environments such as caves or collapsed buildings. Current systems, however, have difficulty in dealing with the large amount of obstacles inherent to such environments. Collisions with obstacles generally result in crashes from which the platform can no longer recover. This paper presents a method to design active uprighting mechanisms for protected rotorcraft-type flying robots that allow them to become upright and subsequently take off again after an otherwise mission-ending collision. This method is demonstrated on a tailsitter flying robot, which is capable of consistently uprighting after falling on its side using a spring-based “leg” and returning to the air to continue its mission.