Author name cluster

Bradley Hamner

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

1 author row

IROS Conference 2012 Conference Paper

A practical obstacle detection system for autonomous orchard vehicles

Gustavo Medeiros Freitas
Bradley Hamner
Marcel Bergerman
Sanjiv Singh

Safe robot navigation in tree fruit orchards requires that the vehicle be capable of robustly navigating between rows of trees and turning from one aisle to another; that the vehicle be dynamically stable, especially when carrying workers; and that the vehicle be able to detect obstacles on its way and adjust its speed accordingly. In this paper we address the latter, in particular the problem of detecting people and apple bins in the aisles between rows. One of our requirements is that the obstacle avoidance subsystem shouldn't add to the robot's hardware cost, so as to keep the acquisition cost to growers as low as possible. Therefore, we confine ourselves to solutions that use only the sensor suite already installed on the robot for navigation-in our case, a laser scanner, low-cost inertial measurement unit, and steering and wheel encoders. Our methodology is based on the classification and clustering of registered 3D points as obstacles. In the current implementation, obstacle avoidance takes in 3D point clouds collected in apple orchards and generates an off-line assessment of obstacle position. Tests conducted at our experimental orchard-like environment in Pittsburgh and an actual apple orchard in Washington state indicate that the method is able to detect people and bins located along the vehicle path. Stretch tests indicate that it is also capable of dealing with objects as small as 15 cm tall as long as they aren't covered by grass, and to detect people crossing the aisles at walking speed.

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ICRA Conference 2012 Conference Paper

Results with autonomous vehicles operating in specialty crops

Marcel Bergerman
Sanjiv Singh
Bradley Hamner

Specialty crops constitute a $45 billion/year industry. As opposed to crops such as wheat, cotton, corn and soybean, they are characterized by the need for intensive cultivation. Specialty crops growers currently face serious labor cost and availability problems, and few technological solutions exist to increase their efficiency given the past history of abundant supply of low-cost labor. This leads to an opportunity to use recent technological advances to not only increase efficiency and reduce labor costs in specialty crops production but also to support a domestic engineering solutions industry for specialty crops. We envision a family of reconfigurable vehicles that can be rapidly tasked to automate or augment pruning, thinning, harvesting, mowing, spraying, etc. They would share a common sensing and computing infrastructure, allowing applications created for one to be easily transferable to others - much like software applications today are transferable from one computer to another. In this paper we describe our work over the last three years designing and deploying a family of such vehicles, the Autonomous Prime Movers (APMs). The five vehicles completed so far have traveled autonomously over 300 km in research and commercial tree fruit orchards; preliminary results in time trials conducted by extension educators indicate efficiency gains of up to 58%.

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IROS Conference 2009 Conference Paper

Mobile robotic dynamic tracking for assembly tasks

Bradley Hamner
Seth Koterba
Jane Shi
Reid G. Simmons
Sanjiv Singh

Traditional industrial robots have been widely used in automotive manufacturing for nearly 30 years. However, there have been very few attempts to automate mobile robotic systems for final assembly operations, despite their potential for high flexibility and capability. This paper focuses on methods of tracking a dynamic moving vehicle that is similar to the vehicle body on a moving assembly line. We have investigated two tracking methods, one using a laser scanner and the other using a visual fiducial marker. We have also studied the tracking performance of a mobile base using the pure pursuit algorithm with low pass filtering. Experimental results are presented to illustrate the remaining main challenges in achieving robotic assembly on moving assembly lines.

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IROS Conference 2006 Conference Paper

Learning to Drive Among Obstacles

Bradley Hamner
Sebastian A. Scherer
Sanjiv Singh

This paper reports on an outdoor mobile robot that learns to avoid collisions by observing a human driver operate a vehicle equipped with sensors that continuously produce a map of the local environment. We have implemented steering control that models human behavior in trying to avoid obstacles while trying to follow a desired path. Here we present the formulation for this control system and its independent parameters, and then show how these parameters can be automatically estimated by observation of a human driver. We present results from experiments with a vehicle (both real and simulated) that avoids obstacles while following a prescribed path at speeds up to 4 m/sec. We compare the proposed method with another method based on principal component analysis, a commonly used learning technique. We find that the proposed method generalizes well and is capable of learning from a small number of examples

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IROS Conference 2003 Conference Paper

Motion planning for a mobile manipulator with imprecise locomotion

Dong Hun Shin
Bradley Hamner
Sanjiv Singh
Myung Hwangbo

This paper presents a motion planning method for mobile manipulators for which the base locomotion is less precise than the manipulator control. In such a case, it is advisable to move the base to discrete poses from which the manipulator can be deployed to cover a prescribed trajectory. The proposed method finds base poses that not only cover the trajectory but also meet constraints on a measure of manipulability. We propose a variant of the conventional manipulability measure that is suited to the trajectory control of the end effector of the mobile manipulator along an arbitrary curve in three space. Results with implementation on a mobile manipulator are discussed.

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