Braden Stenning

Visual Teach and Repeat using appearance-based lidar

Visual Teach and Repeat (VT&R) has proven to be an effective method to allow a vehicle to autonomously repeat any previously driven route without the need for a global positioning system. One of the major challenges for a method that relies on visual input to recognize previously visited places is lighting change, as this can make the appearance of a scene look drastically different. For this reason, passive sensors, such as cameras, are not ideal for outdoor environments with inconsistent/inadequate light. However, camera-based systems have been very successful for localization and mapping in outdoor, unstructured terrain, which can be largely attributed to the use of sparse, appearance-based computer vision techniques. Thus, in an effort to achieve lighting invariance and to continue to exploit the heritage of the appearance-based vision techniques traditionally used with cameras, this paper presents the first VT&R system that uses appearance-based techniques with laser scanners for motion estimation. The system has been field tested in a planetary analogue environment for an entire diurnal cycle, covering more than 11km with an autonomy rate of 99.7% of the distance traveled.

Planning using a Network of Reusable Paths: A Physical Embodiment of a Rapidly Exploring Random Tree

Growing a network of reusable paths is a novel approach to navigation that allows a mobile robot to autonomously seek distant goals in unmapped, GPS-denied environments, which may make it particularly well-suited to rovers used for planetary exploration. A network of reusable paths is an extension to visual-teach-and-repeat systems; instead of a simple chain of poses, there is an arbitrary network. This allows the robot to return to any pose it has previously visited, and it lets a robot plan to reuse previous paths. This paradigm results in closer goal acquisition (through reduced localization error) and a more robust approach to exploration with a mobile robot. It also allows a rover to return a sample to an ascent vehicle with a single command. We show that our network-of-reusable-paths approach is a physical embodiment of the popular rapidly exploring random tree (RRT) planner. Simulation results are presented along with the results from two different robotic test systems. These test systems drove over 14 km in planetary analog environments.

Path planning on a network of paths

This work presents the first step toward an innovative new navigation framework, based on growing a network of reusable paths, to allow a mobile robot to autonomously explore unmapped, GPS-denied, extreme environments. The paradigm (i) results in closer goal acquisition (through reduced localization error), (ii) allows for effective recovery from dead-ends or unproductive routes, (iii) avoids terrain-assessment artifacts due to map merging, and (iv) eliminates the possibility of a robot being unable to find any safe path from the current pose, even when there is one. Extensive simulation and preliminary hardware results are provided.

Exploiting Reusable Paths in Mobile Robotics: Benefits and Challenges for Long-term Autonomy

Visual-teach-and-repeat (VT&R) systems have proven extremely useful for practical robot autonomy where the global positioning system is either unavailable or unreliable, examples include tramming for underground mining using a planar laser scanner as well as a return-to-lander function for planetary exploration using a stereo-or laser-based camera. By embedding local appearance/metric information along an arbitrarily long path, it becomes possible to re-drive the path without the need for a single privileged coordinate frame and using only modest computational resources. For a certain class of long-term autonomy problems (e.g., repeatable long-range driving), VT&R appears to offer a simple yet scalable solution. Beyond single paths, we envision that networks of reusable paths could be established and shared from one robot to another to enable practical tasks such as surveillance, delivery (e.g., mail, hospitals, factories, warehouses), worksite operations (e.g., construction, mining), and autonomous roadways. However, for lifelong operations on reusable paths, robustness to a variety of environmental changes, both transient and permanent, is required. In this paper, we relate our experiences and lessons learned with the three above-mentioned implementations of VT&R systems. Based on this, we enumerate both the benefits and challenges of reusable paths that we see moving forwards. We discuss one such challenge, lighting-invariance, in detail and present our progess in overcoming it.

Path planning with variable-fidelity terrain assessment

Terrain assessment and path planning are intrinsically linked. There exist a variety of terrain-assessment algorithms and these methods follow the trend of low-fidelity at low-cost and high-fidelity at high-cost. We present a modular path-planning algorithm that uses a hierarchy of terrain-assessment methods; from low-fidelity to high-fidelity. Using all the available sensor data, the visible terrain is assessed with the low-fidelity, low-cost method. The decision to assess a piece of terrain with the high-fidelity, high-cost method is made considering potential path benefits and the cost of assessment. The result is a lower combined cost of the path and terrain assessment that exploits the capabilities of the robot chassis where prudent. We demonstrate the technique on a large number of simulated path-planning problems using fractal terrain, as well as provide preliminary results from an experimental field test carried out on Devon Island, Canada.

Field testing of a rover guidance, navigation, and control architecture to support a ground-ice prospecting mission to Mars

This paper provides an overview of a rover guidance, navigation, and control (GN&C) architecture being developed to support a ground-ice prospecting mission to Mars. The main contribution of this paper is to detail an integrated field campaign that demonstrates the viability of the key rover GN&C techniques needed to carry out this mission. Tests were conducted on Devon Island in the Canadian High Arctic during the summer of 2009, wherein a large field robot was driven on real polygonal terrain (a landform of interest on Mars). Lessons learned and recommendations for future work are provided.

Towards Autonomous Mobile Robots for the Exploration of Steep Terrain

Steep, natural terrain offers excellent opportunities for scientific investigations into the composition and history of Mars and other planetary bodies. In this paper, we present a prototype tethered robot, vScout (vertical scout), capable of operating in steep, rugged terrain. The primary purpose of this vehicle is to support field geologists conducting research on cliffs, in canyons, and on crater walls. However, the long-term vision is to develop a system suitable for planetary exploration (and more diverse terrestrial applications). Unlike other systems for exploration in steep terrain, vScout has demonstrated autonomous operation on steep surfaces by making use of a network of reusable paths and visual teach & repeat. Here we describe the first vScout prototype and our experiences with it. We also outline some challenges and the directions we intend to take with this research.

Devon Island as a Proving Ground for Planetary Rovers

The future of space exploration will be increasingly surface-based and extended-duration. Planetary rovers, both manned and autonomous, will play vital roles in transporting instruments, astronauts, and equipment across rugged and unfamiliar surfaces. To enable this vision, it is advisable to deploy prototype rover vehicles in analog environments on Earth, in order to learn how best to use these tools. Devon Island, in the Canadian High Arctic, has been used as a proving ground for planetary rovers, due to its vast scale, variety of topography/geology, challenging lighting, lack of vegetation, existing infrastructure at the well-established Haughton- Mars Project Research Station, and wealth of interesting scientific mission objectives. In this paper we review the suitability of using Devon Island for the continued testing of planetary rovers; several examples of previously conducted tests are provided. We conclude that despite the typical logistical challenges associated with remote field work, Devon Island should be considered a strong candidate for ongoing rover field deployments.