The Defence, Peace, Safety and Security (DPSS) competency area within the Council for Scientific and
Industrial Research (CSIR) has identified the need for the development of a robot that can operate in
almost any land-based environment. Legged robots, especially hexapod (six-legged) robots present a
wide variety of advantages that can be utilised in this environment and is identified as a feasible
solution.
The biggest advantage and main reason for the development of legged robots over mobile (wheeled)
robots, is their ability to navigate in uneven, unstructured terrain. However, due to the complicated
control algorithms needed by a legged robot, most literature only focus on navigation in even or
relatively even terrains. This is seen as the main limitation with regards to the development of legged
robot applications. For navigation in unstructured terrain, postural controllers of legged robots need
fast and precise knowledge about the state of the robot they are regulating. The speed and accuracy
of the state estimation of a legged robot is therefore very important.
Even though state estimation for mobile robots has been studied thoroughly, limited research is
available on state estimation with regards to legged robots. Compared to mobile robots, locomotion
of legged robots make use of intermitted ground contacts. Therefore, stability is a main concern when
navigating in unstructured terrain. In order to control the stability of a legged robot, six degrees of
freedom information is needed about the base of the robot platform. This information needs to be
estimated using measurements from the robot’s sensory system.
A sensory system of a robot usually consist of multiple sensory devices on board of the robot.
However, legged robots have limited payload capacities and therefore the amount of sensory devices
on a legged robot platform should be kept to a minimum. Furthermore, exteroceptive sensory devices
commonly used in state estimation, such as a GPS or cameras, are not suitable when navigating in
unstructured and unknown terrain. The control and localisation of a legged robot should therefore
only depend on proprioceptive sensors. The need for the development of a reliable state estimation
framework (that only relies on proprioceptive information) for a low-cost, commonly available
hexapod robot is identified. This will accelerate the process for control algorithm development.
In this study this need is addressed. Common proprioceptive sensors are integrated on a commercial
low-cost hexapod robot to develop the robot platform used in this study. A state estimation
framework for legged robots is used to develop a state estimation methodology for the hexapod
platform. A kinematic model is also derived and verified for the platform, and measurement models
are derived to address possible errors and noise in sensor measurements. The state estimation
methodology makes use of an Extended Kalman filter to fuse the robots kinematics with
measurements from an IMU. The needed state estimation equations are also derived and
implemented in Matlab®.
The state estimation methodology developed is then tested with multiple experiments using the robot
platform. In these experiments the robot platform captures the sensory data with a data acquisition
method developed while it is being tracked with a Vicon motion capturing system. The sensor data is
then used as an input to the state estimation equations in Matlab® and the results are compared to
the ground-truth measurement outputs of the Vicon system. The results of these experiments show
very accurate estimation of the robot and therefore validate the state estimation methodology and
this study. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015
| Identifer | oai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/15374 |
| Date | January 2014 |
| Creators | Lubbe, Estelle |
| Source Sets | North-West University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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