Tactile Sensing and Terrain-Based Gait Control for Small Legged Robots

AbstractRobotic assembly tasks are typically implemented in static settings in which parts are kept at fixed locations by making use of part holders. Very few works deal with the problem of moving parts in industrial assembly applications. However, having autonomous robots that are able to execute assembly tasks in dynamic environments could lead to more flexible facilities with reduced implementation efforts for individual products. In this paper, we present a general approach towards autonomous robotic assembly that combines visual and intrinsic tactile sensing to continuously track parts within a single Bayesian framework. Based on this, it is possible to implement object-centric assembly skills that are guided by the estimated poses of the parts, including cases where occlusions block the vision system. In particular, we investigate the application of this approach for peg-in-hole assembly. A tilt-and-align strategy is implemented using a Cartesian impedance controller, and combined with an adaptive path executor. Experimental results with multiple part combinations are provided and analyzed in detail.

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Diversity-based design assist for large legged robots

Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion ◽

10.1145/3377929.3389950 ◽

2020 ◽

Author(s):

Gerard Howard ◽

Thomas Lowe ◽

Wade Geles

Keyword(s):

Legged Robots

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Novel Response Acquisition Method for Enhancing Spatial Resolution in Capacitive Tactile Sensing Array

IEEE Sensors Journal ◽

10.1109/jsen.2020.3043465 ◽

2020 ◽

pp. 1-1

Author(s):

Shi-Yu Ke ◽

Yu-Wen Chen ◽

Cheng-Yao Lo ◽

Cheng-Yao Lo

Keyword(s):

Spatial Resolution ◽

Tactile Sensing ◽

Response Acquisition ◽

Acquisition Method

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Stability-Guaranteed and High Terrain Adaptability Static Gait for Quadruped Robots

Sensors ◽

10.3390/s20174911 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4911

Author(s):

Qian Hao ◽

Zhaoba Wang ◽

Junzheng Wang ◽

Guangrong Chen

Keyword(s):

Impedance Control ◽

Stability Margin ◽

Planning Method ◽

Legged Robots ◽

Gait Planning ◽

Quadruped Locomotion ◽

Quadruped Robots ◽

Adjustment Strategy ◽

Compliant Behavior ◽

The Stability

Stability is a prerequisite for legged robots to execute tasks and traverse rough terrains. To guarantee the stability of quadruped locomotion and improve the terrain adaptability of quadruped robots, a stability-guaranteed and high terrain adaptability static gait for quadruped robots is addressed. Firstly, three chosen stability-guaranteed static gaits: intermittent gait 1&2 and coordinated gait are investigated. In addition, then the static gait: intermittent gait 1, which is with the biggest stability margin, is chosen to do a further research about quadruped robots walking on rough terrains. Secondly, a position/force based impedance control is employed to achieve a compliant behavior of quadruped robots on rough terrains. Thirdly, an exploratory gait planning method on uneven terrains with touch sensing and an attitude-position adjustment strategy with terrain estimation are proposed to improve the terrain adaptability of quadruped robots. Finally, the proposed methods are validated by simulations.

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Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Frontiers of Mechanical Engineering ◽

10.1007/s11465-020-0623-1 ◽

2021 ◽

Author(s):

Yue Zhao ◽

Feng Gao ◽

Qiao Sun ◽

Yunpeng Yin

Keyword(s):

Legged Robots ◽

Measurement Unit ◽

Support Vector ◽

Hexapod Robot ◽

Terrain Classification ◽

Adaptive Locomotion ◽

Joint Torques ◽

Active Compliance ◽

Outdoor Environments ◽

The Stability

AbstractLegged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

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